id	sid	tid	token	lemma	pos
ajst-25576	1	1	academic	academic	ADJ
ajst-25576	1	2	journal	journal	NOUN
ajst-25576	1	3	of	of	ADP
ajst-25576	1	4	science	science	NOUN
ajst-25576	1	5	and	and	CCONJ
ajst-25576	1	6	technology	technology	NOUN
ajst-25576	1	7	issn	issn	NOUN
ajst-25576	1	8	:	:	PUNCT
ajst-25576	1	9	2771	2771	NUM
ajst-25576	1	10	-	-	SYM
ajst-25576	1	11	3032	3032	NUM
ajst-25576	1	12	|	|	NOUN
ajst-25576	1	13	vol	vol	NOUN
ajst-25576	1	14	.	.	PROPN
ajst-25576	2	1	12	12	NUM
ajst-25576	2	2	,	,	PUNCT
ajst-25576	2	3	no	no	INTJ
ajst-25576	2	4	.	.	NOUN
ajst-25576	2	5	2	2	NUM
ajst-25576	2	6	,	,	PUNCT
ajst-25576	2	7	2024	2024	NUM
ajst-25576	2	8	72	72	NUM
ajst-25576	2	9	simulation	simulation	NOUN
ajst-25576	2	10	and	and	CCONJ
ajst-25576	2	11	research	research	NOUN
ajst-25576	2	12	on	on	ADP
ajst-25576	2	13	pid	pid	NOUN
ajst-25576	2	14	parameter	parameter	NOUN
ajst-25576	2	15	tuning	tuning	NOUN
ajst-25576	2	16	based	base	VERB
ajst-25576	2	17	on	on	ADP
ajst-25576	2	18	improved	improved	ADJ
ajst-25576	2	19	beetle	beetle	NOUN
ajst-25576	2	20	antennae	antennae	NOUN
ajst-25576	2	21	search	search	NOUN
ajst-25576	2	22	algorithm	algorithm	NOUN
ajst-25576	2	23	peng	peng	PROPN
ajst-25576	2	24	zhang	zhang	PROPN
ajst-25576	2	25	xi	xi	X
ajst-25576	2	26	'	'	PUNCT
ajst-25576	2	27	an	an	DET
ajst-25576	2	28	shiyou	shiyou	PROPN
ajst-25576	2	29	university	university	NOUN
ajst-25576	2	30	,	,	PUNCT
ajst-25576	2	31	xi	xi	ADP
ajst-25576	2	32	'	'	PUNCT
ajst-25576	2	33	an	an	DET
ajst-25576	2	34	shanxi	shanxi	NOUN
ajst-25576	2	35	,	,	PUNCT
ajst-25576	2	36	710000	710000	NUM
ajst-25576	2	37	,	,	PUNCT
ajst-25576	2	38	china	china	PROPN
ajst-25576	2	39	abstract	abstract	NOUN
ajst-25576	2	40	:	:	PUNCT
ajst-25576	2	41	the	the	DET
ajst-25576	2	42	traditional	traditional	ADJ
ajst-25576	2	43	pid	pid	NOUN
ajst-25576	2	44	parameter	parameter	NOUN
ajst-25576	2	45	tuning	tuning	NOUN
ajst-25576	2	46	method	method	NOUN
ajst-25576	2	47	has	have	VERB
ajst-25576	2	48	the	the	DET
ajst-25576	2	49	problem	problem	NOUN
ajst-25576	2	50	that	that	SCONJ
ajst-25576	2	51	it	it	PRON
ajst-25576	2	52	is	be	AUX
ajst-25576	2	53	difficult	difficult	ADJ
ajst-25576	2	54	to	to	PART
ajst-25576	2	55	achieve	achieve	VERB
ajst-25576	2	56	optimal	optimal	ADJ
ajst-25576	2	57	performance	performance	NOUN
ajst-25576	2	58	and	and	CCONJ
ajst-25576	2	59	even	even	ADV
ajst-25576	2	60	lead	lead	VERB
ajst-25576	2	61	to	to	ADP
ajst-25576	2	62	system	system	NOUN
ajst-25576	2	63	instability	instability	NOUN
ajst-25576	2	64	.	.	PUNCT
ajst-25576	3	1	in	in	ADP
ajst-25576	3	2	order	order	NOUN
ajst-25576	3	3	to	to	PART
ajst-25576	3	4	overcome	overcome	VERB
ajst-25576	3	5	these	these	DET
ajst-25576	3	6	problems	problem	NOUN
ajst-25576	3	7	,	,	PUNCT
ajst-25576	3	8	an	an	DET
ajst-25576	3	9	improved	improve	VERB
ajst-25576	3	10	beetle	beetle	NOUN
ajst-25576	3	11	antennae	antennae	NOUN
ajst-25576	3	12	search	search	NOUN
ajst-25576	3	13	(	(	PUNCT
ajst-25576	3	14	bas	bas	NOUN
ajst-25576	3	15	)	)	PUNCT
ajst-25576	3	16	algorithm	algorithm	NOUN
ajst-25576	3	17	is	be	AUX
ajst-25576	3	18	proposed	propose	VERB
ajst-25576	3	19	in	in	ADP
ajst-25576	3	20	this	this	DET
ajst-25576	3	21	paper	paper	NOUN
ajst-25576	3	22	.	.	PUNCT
ajst-25576	4	1	by	by	ADP
ajst-25576	4	2	dynamically	dynamically	ADV
ajst-25576	4	3	adjusting	adjust	VERB
ajst-25576	4	4	the	the	DET
ajst-25576	4	5	step	step	NOUN
ajst-25576	4	6	size	size	NOUN
ajst-25576	4	7	,	,	PUNCT
ajst-25576	4	8	introducing	introduce	VERB
ajst-25576	4	9	random	random	ADJ
ajst-25576	4	10	disturbance	disturbance	NOUN
ajst-25576	4	11	and	and	CCONJ
ajst-25576	4	12	elite	elite	ADJ
ajst-25576	4	13	reservation	reservation	NOUN
ajst-25576	4	14	strategy	strategy	NOUN
ajst-25576	4	15	,	,	PUNCT
ajst-25576	4	16	the	the	DET
ajst-25576	4	17	global	global	ADJ
ajst-25576	4	18	optimization	optimization	NOUN
ajst-25576	4	19	ability	ability	NOUN
ajst-25576	4	20	and	and	CCONJ
ajst-25576	4	21	convergence	convergence	NOUN
ajst-25576	4	22	speed	speed	NOUN
ajst-25576	4	23	of	of	ADP
ajst-25576	4	24	the	the	DET
ajst-25576	4	25	algorithm	algorithm	NOUN
ajst-25576	4	26	are	be	AUX
ajst-25576	4	27	significantly	significantly	ADV
ajst-25576	4	28	improved	improve	VERB
ajst-25576	4	29	.	.	PUNCT
ajst-25576	5	1	in	in	ADP
ajst-25576	5	2	this	this	DET
ajst-25576	5	3	study	study	NOUN
ajst-25576	5	4	,	,	PUNCT
ajst-25576	5	5	the	the	DET
ajst-25576	5	6	improved	improved	ADJ
ajst-25576	5	7	bas	bas	PROPN
ajst-25576	5	8	algorithm	algorithm	NOUN
ajst-25576	5	9	is	be	AUX
ajst-25576	5	10	applied	apply	VERB
ajst-25576	5	11	to	to	ADP
ajst-25576	5	12	the	the	DET
ajst-25576	5	13	parameter	parameter	NOUN
ajst-25576	5	14	tuning	tuning	NOUN
ajst-25576	5	15	of	of	ADP
ajst-25576	5	16	pid	pid	NOUN
ajst-25576	5	17	controller	controller	NOUN
ajst-25576	5	18	.	.	PUNCT
ajst-25576	6	1	by	by	ADP
ajst-25576	6	2	defining	define	VERB
ajst-25576	6	3	an	an	DET
ajst-25576	6	4	objective	objective	ADJ
ajst-25576	6	5	function	function	NOUN
ajst-25576	6	6	that	that	PRON
ajst-25576	6	7	comprehensively	comprehensively	ADV
ajst-25576	6	8	considers	consider	VERB
ajst-25576	6	9	the	the	DET
ajst-25576	6	10	performance	performance	NOUN
ajst-25576	6	11	indexes	index	NOUN
ajst-25576	6	12	such	such	ADJ
ajst-25576	6	13	as	as	ADP
ajst-25576	6	14	system	system	NOUN
ajst-25576	6	15	overshoot	overshoot	NOUN
ajst-25576	6	16	,	,	PUNCT
ajst-25576	6	17	regulation	regulation	NOUN
ajst-25576	6	18	time	time	NOUN
ajst-25576	6	19	and	and	CCONJ
ajst-25576	6	20	steady	steady	ADJ
ajst-25576	6	21	-	-	PUNCT
ajst-25576	6	22	state	state	NOUN
ajst-25576	6	23	error	error	NOUN
ajst-25576	6	24	,	,	PUNCT
ajst-25576	6	25	the	the	DET
ajst-25576	6	26	algorithm	algorithm	NOUN
ajst-25576	6	27	is	be	AUX
ajst-25576	6	28	used	use	VERB
ajst-25576	6	29	for	for	ADP
ajst-25576	6	30	iterative	iterative	ADJ
ajst-25576	6	31	search	search	NOUN
ajst-25576	6	32	to	to	PART
ajst-25576	6	33	determine	determine	VERB
ajst-25576	6	34	the	the	DET
ajst-25576	6	35	optimal	optimal	ADJ
ajst-25576	6	36	pid	pid	NOUN
ajst-25576	6	37	parameter	parameter	NOUN
ajst-25576	6	38	combination	combination	NOUN
ajst-25576	6	39	.	.	PUNCT
ajst-25576	7	1	the	the	DET
ajst-25576	7	2	experiment	experiment	NOUN
ajst-25576	7	3	uses	use	VERB
ajst-25576	7	4	matlab	matlab	PROPN
ajst-25576	7	5	/	/	SYM
ajst-25576	7	6	simulink	simulink	PROPN
ajst-25576	7	7	platform	platform	NOUN
ajst-25576	7	8	for	for	ADP
ajst-25576	7	9	simulation	simulation	NOUN
ajst-25576	7	10	,	,	PUNCT
ajst-25576	7	11	taking	take	VERB
ajst-25576	7	12	the	the	DET
ajst-25576	7	13	second	second	ADJ
ajst-25576	7	14	-	-	PUNCT
ajst-25576	7	15	order	order	NOUN
ajst-25576	7	16	system	system	NOUN
ajst-25576	7	17	as	as	ADP
ajst-25576	7	18	the	the	DET
ajst-25576	7	19	controlled	control	VERB
ajst-25576	7	20	object	object	NOUN
ajst-25576	7	21	,	,	PUNCT
ajst-25576	7	22	and	and	CCONJ
ajst-25576	7	23	simulating	simulate	VERB
ajst-25576	7	24	different	different	ADJ
ajst-25576	7	25	system	system	NOUN
ajst-25576	7	26	dynamics	dynamic	NOUN
ajst-25576	7	27	by	by	ADP
ajst-25576	7	28	changing	change	VERB
ajst-25576	7	29	system	system	NOUN
ajst-25576	7	30	parameters	parameter	NOUN
ajst-25576	7	31	.	.	PUNCT
ajst-25576	8	1	the	the	DET
ajst-25576	8	2	findings	finding	NOUN
ajst-25576	8	3	from	from	ADP
ajst-25576	8	4	the	the	DET
ajst-25576	8	5	experiments	experiment	NOUN
ajst-25576	8	6	indicate	indicate	VERB
ajst-25576	8	7	that	that	SCONJ
ajst-25576	8	8	the	the	DET
ajst-25576	8	9	improved	improved	ADJ
ajst-25576	8	10	bas	bas	PROPN
ajst-25576	8	11	algorithm	algorithm	NOUN
ajst-25576	8	12	outperforms	outperform	VERB
ajst-25576	8	13	traditional	traditional	ADJ
ajst-25576	8	14	methods	method	NOUN
ajst-25576	8	15	in	in	ADP
ajst-25576	8	16	terms	term	NOUN
ajst-25576	8	17	of	of	ADP
ajst-25576	8	18	convergence	convergence	NOUN
ajst-25576	8	19	speed	speed	NOUN
ajst-25576	8	20	,	,	PUNCT
ajst-25576	8	21	optimization	optimization	NOUN
ajst-25576	8	22	outcomes	outcome	NOUN
ajst-25576	8	23	,	,	PUNCT
ajst-25576	8	24	and	and	CCONJ
ajst-25576	8	25	stability	stability	NOUN
ajst-25576	8	26	.	.	PUNCT
ajst-25576	9	1	with	with	ADP
ajst-25576	9	2	an	an	DET
ajst-25576	9	3	identical	identical	ADJ
ajst-25576	9	4	number	number	NOUN
ajst-25576	9	5	of	of	ADP
ajst-25576	9	6	iterations	iteration	NOUN
ajst-25576	9	7	,	,	PUNCT
ajst-25576	9	8	the	the	DET
ajst-25576	9	9	refined	refined	ADJ
ajst-25576	9	10	algorithm	algorithm	NOUN
ajst-25576	9	11	yields	yield	VERB
ajst-25576	9	12	a	a	DET
ajst-25576	9	13	lower	low	ADJ
ajst-25576	9	14	objective	objective	ADJ
ajst-25576	9	15	function	function	NOUN
ajst-25576	9	16	value	value	NOUN
ajst-25576	9	17	,	,	PUNCT
ajst-25576	9	18	reduced	reduce	VERB
ajst-25576	9	19	overshoot	overshoot	NOUN
ajst-25576	9	20	,	,	PUNCT
ajst-25576	9	21	shortened	shorten	VERB
ajst-25576	9	22	adjustment	adjustment	NOUN
ajst-25576	9	23	duration	duration	NOUN
ajst-25576	9	24	,	,	PUNCT
ajst-25576	9	25	and	and	CCONJ
ajst-25576	9	26	diminished	diminish	VERB
ajst-25576	9	27	steady	steady	ADJ
ajst-25576	9	28	-	-	PUNCT
ajst-25576	9	29	state	state	NOUN
ajst-25576	9	30	error	error	NOUN
ajst-25576	9	31	.	.	PUNCT
ajst-25576	10	1	the	the	DET
ajst-25576	10	2	pid	pid	NOUN
ajst-25576	10	3	parameter	parameter	NOUN
ajst-25576	10	4	tuning	tuning	NOUN
ajst-25576	10	5	technique	technique	NOUN
ajst-25576	10	6	,	,	PUNCT
ajst-25576	10	7	grounded	ground	VERB
ajst-25576	10	8	on	on	ADP
ajst-25576	10	9	the	the	DET
ajst-25576	10	10	improved	improve	VERB
ajst-25576	10	11	bas	bas	PROPN
ajst-25576	10	12	algorithm	algorithm	NOUN
ajst-25576	10	13	presented	present	VERB
ajst-25576	10	14	in	in	ADP
ajst-25576	10	15	this	this	DET
ajst-25576	10	16	research	research	NOUN
ajst-25576	10	17	,	,	PUNCT
ajst-25576	10	18	not	not	PART
ajst-25576	10	19	only	only	ADV
ajst-25576	10	20	maintains	maintain	VERB
ajst-25576	10	21	the	the	DET
ajst-25576	10	22	simplicity	simplicity	NOUN
ajst-25576	10	23	inherent	inherent	ADJ
ajst-25576	10	24	to	to	ADP
ajst-25576	10	25	the	the	DET
ajst-25576	10	26	conventional	conventional	ADJ
ajst-25576	10	27	bas	bas	PROPN
ajst-25576	10	28	algorithm	algorithm	NOUN
ajst-25576	10	29	but	but	CCONJ
ajst-25576	10	30	also	also	ADV
ajst-25576	10	31	markedly	markedly	ADV
ajst-25576	10	32	boosts	boost	VERB
ajst-25576	10	33	its	its	PRON
ajst-25576	10	34	global	global	ADJ
ajst-25576	10	35	optimization	optimization	NOUN
ajst-25576	10	36	capability	capability	NOUN
ajst-25576	10	37	and	and	CCONJ
ajst-25576	10	38	convergence	convergence	NOUN
ajst-25576	10	39	rate	rate	NOUN
ajst-25576	10	40	.	.	PUNCT
ajst-25576	11	1	this	this	PRON
ajst-25576	11	2	offers	offer	VERB
ajst-25576	11	3	innovative	innovative	ADJ
ajst-25576	11	4	perspectives	perspective	NOUN
ajst-25576	11	5	and	and	CCONJ
ajst-25576	11	6	techniques	technique	NOUN
ajst-25576	11	7	for	for	ADP
ajst-25576	11	8	optimizing	optimize	VERB
ajst-25576	11	9	industrial	industrial	ADJ
ajst-25576	11	10	control	control	NOUN
ajst-25576	11	11	systems	system	NOUN
ajst-25576	11	12	.	.	PUNCT
ajst-25576	12	1	keywords	keyword	NOUN
ajst-25576	12	2	:	:	PUNCT
ajst-25576	12	3	pid	pid	NUM
ajst-25576	12	4	parameter	parameter	NOUN
ajst-25576	12	5	tuning	tuning	NOUN
ajst-25576	12	6	;	;	PUNCT
ajst-25576	12	7	simulation	simulation	NOUN
ajst-25576	12	8	;	;	PUNCT
ajst-25576	12	9	improved	improve	VERB
ajst-25576	12	10	beetle	beetle	NOUN
ajst-25576	12	11	antennae	antennae	NOUN
ajst-25576	12	12	search	search	NOUN
ajst-25576	12	13	algorithm	algorithm	NOUN
ajst-25576	12	14	.	.	PUNCT
ajst-25576	13	1	1	1	X
ajst-25576	13	2	.	.	X
ajst-25576	13	3	introduction	introduction	NOUN
ajst-25576	13	4	as	as	ADP
ajst-25576	13	5	the	the	DET
ajst-25576	13	6	core	core	NOUN
ajst-25576	13	7	component	component	NOUN
ajst-25576	13	8	in	in	ADP
ajst-25576	13	9	the	the	DET
ajst-25576	13	10	field	field	NOUN
ajst-25576	13	11	of	of	ADP
ajst-25576	13	12	automatic	automatic	ADJ
ajst-25576	13	13	control	control	NOUN
ajst-25576	13	14	,	,	PUNCT
ajst-25576	13	15	pid	pid	DET
ajst-25576	13	16	controller	controller	NOUN
ajst-25576	13	17	has	have	AUX
ajst-25576	13	18	always	always	ADV
ajst-25576	13	19	occupied	occupy	VERB
ajst-25576	13	20	a	a	DET
ajst-25576	13	21	decisive	decisive	ADJ
ajst-25576	13	22	position	position	NOUN
ajst-25576	13	23	in	in	ADP
ajst-25576	13	24	industrial	industrial	ADJ
ajst-25576	13	25	control	control	NOUN
ajst-25576	13	26	system	system	NOUN
ajst-25576	13	27	.	.	PUNCT
ajst-25576	14	1	it	it	PRON
ajst-25576	14	2	can	can	AUX
ajst-25576	14	3	effectively	effectively	ADV
ajst-25576	14	4	and	and	CCONJ
ajst-25576	14	5	accurately	accurately	ADV
ajst-25576	14	6	control	control	VERB
ajst-25576	14	7	all	all	DET
ajst-25576	14	8	kinds	kind	NOUN
ajst-25576	14	9	of	of	ADP
ajst-25576	14	10	dynamic	dynamic	ADJ
ajst-25576	14	11	systems	system	NOUN
ajst-25576	14	12	through	through	ADP
ajst-25576	14	13	the	the	DET
ajst-25576	14	14	synergistic	synergistic	ADJ
ajst-25576	14	15	effect	effect	NOUN
ajst-25576	14	16	of	of	ADP
ajst-25576	14	17	proportion	proportion	NOUN
ajst-25576	14	18	,	,	PUNCT
ajst-25576	14	19	integration	integration	NOUN
ajst-25576	14	20	and	and	CCONJ
ajst-25576	14	21	differentiation	differentiation	NOUN
ajst-25576	14	22	,	,	PUNCT
ajst-25576	14	23	thus	thus	ADV
ajst-25576	14	24	ensuring	ensure	VERB
ajst-25576	14	25	the	the	DET
ajst-25576	14	26	smooth	smooth	ADJ
ajst-25576	14	27	operation	operation	NOUN
ajst-25576	14	28	of	of	ADP
ajst-25576	14	29	industrial	industrial	ADJ
ajst-25576	14	30	processes	process	NOUN
ajst-25576	14	31	.	.	PUNCT
ajst-25576	15	1	however	however	ADV
ajst-25576	15	2	,	,	PUNCT
ajst-25576	15	3	the	the	DET
ajst-25576	15	4	performance	performance	NOUN
ajst-25576	15	5	of	of	ADP
ajst-25576	15	6	pid	pid	NOUN
ajst-25576	15	7	controller	controller	NOUN
ajst-25576	15	8	is	be	AUX
ajst-25576	15	9	highly	highly	ADV
ajst-25576	15	10	dependent	dependent	ADJ
ajst-25576	15	11	on	on	ADP
ajst-25576	15	12	the	the	DET
ajst-25576	15	13	setting	setting	NOUN
ajst-25576	15	14	of	of	ADP
ajst-25576	15	15	its	its	PRON
ajst-25576	15	16	parameters	parameter	NOUN
ajst-25576	15	17	,	,	PUNCT
ajst-25576	15	18	which	which	PRON
ajst-25576	15	19	include	include	VERB
ajst-25576	15	20	proportional	proportional	ADJ
ajst-25576	15	21	coefficient	coefficient	NOUN
ajst-25576	15	22	,	,	PUNCT
ajst-25576	15	23	integral	integral	ADJ
ajst-25576	15	24	coefficient	coefficient	NOUN
ajst-25576	15	25	and	and	CCONJ
ajst-25576	15	26	differential	differential	ADJ
ajst-25576	15	27	coefficient	coefficient	NOUN
ajst-25576	15	28	.	.	PUNCT
ajst-25576	16	1	the	the	DET
ajst-25576	16	2	conventional	conventional	ADJ
ajst-25576	16	3	approach	approach	NOUN
ajst-25576	16	4	to	to	ADP
ajst-25576	16	5	pid	pid	NOUN
ajst-25576	16	6	parameter	parameter	PROPN
ajst-25576	16	7	tuning	tuning	NOUN
ajst-25576	16	8	,	,	PUNCT
ajst-25576	16	9	exemplified	exemplify	VERB
ajst-25576	16	10	by	by	ADP
ajst-25576	16	11	the	the	DET
ajst-25576	16	12	ziegler	ziegler	PROPN
ajst-25576	16	13	-	-	PROPN
ajst-25576	16	14	nichols	nichols	PROPN
ajst-25576	16	15	method	method	NOUN
ajst-25576	16	16	,	,	PUNCT
ajst-25576	16	17	is	be	AUX
ajst-25576	16	18	straightforward	straightforward	ADJ
ajst-25576	16	19	and	and	CCONJ
ajst-25576	16	20	convenient	convenient	ADJ
ajst-25576	16	21	;	;	PUNCT
ajst-25576	16	22	however	however	ADV
ajst-25576	16	23	,	,	PUNCT
ajst-25576	16	24	it	it	PRON
ajst-25576	16	25	frequently	frequently	ADV
ajst-25576	16	26	falls	fall	VERB
ajst-25576	16	27	short	short	ADJ
ajst-25576	16	28	in	in	ADP
ajst-25576	16	29	guaranteeing	guarantee	VERB
ajst-25576	16	30	peak	peak	NOUN
ajst-25576	16	31	system	system	NOUN
ajst-25576	16	32	performance	performance	NOUN
ajst-25576	16	33	and	and	CCONJ
ajst-25576	16	34	may	may	AUX
ajst-25576	16	35	,	,	PUNCT
ajst-25576	16	36	in	in	ADP
ajst-25576	16	37	certain	certain	ADJ
ajst-25576	16	38	instances	instance	NOUN
ajst-25576	16	39	,	,	PUNCT
ajst-25576	16	40	precipitate	precipitate	NOUN
ajst-25576	16	41	system	system	NOUN
ajst-25576	16	42	instability	instability	NOUN
ajst-25576	16	43	[	[	X
ajst-25576	16	44	1	1	NUM
ajst-25576	16	45	-	-	SYM
ajst-25576	16	46	2	2	NUM
ajst-25576	16	47	]	]	PUNCT
ajst-25576	16	48	.	.	PUNCT
ajst-25576	17	1	in	in	ADP
ajst-25576	17	2	the	the	DET
ajst-25576	17	3	recent	recent	ADJ
ajst-25576	17	4	past	past	NOUN
ajst-25576	17	5	,	,	PUNCT
ajst-25576	17	6	coinciding	coincide	VERB
ajst-25576	17	7	with	with	ADP
ajst-25576	17	8	the	the	DET
ajst-25576	17	9	evolution	evolution	NOUN
ajst-25576	17	10	of	of	ADP
ajst-25576	17	11	intelligent	intelligent	ADJ
ajst-25576	17	12	optimization	optimization	NOUN
ajst-25576	17	13	algorithms	algorithm	NOUN
ajst-25576	17	14	,	,	PUNCT
ajst-25576	17	15	an	an	DET
ajst-25576	17	16	increasing	increase	VERB
ajst-25576	17	17	number	number	NOUN
ajst-25576	17	18	of	of	ADP
ajst-25576	17	19	researchers	researcher	NOUN
ajst-25576	17	20	have	have	AUX
ajst-25576	17	21	started	start	VERB
ajst-25576	17	22	to	to	PART
ajst-25576	17	23	delve	delve	VERB
ajst-25576	17	24	into	into	ADP
ajst-25576	17	25	the	the	DET
ajst-25576	17	26	potential	potential	NOUN
ajst-25576	17	27	of	of	ADP
ajst-25576	17	28	applying	apply	VERB
ajst-25576	17	29	these	these	DET
ajst-25576	17	30	algorithms	algorithm	NOUN
ajst-25576	17	31	to	to	ADP
ajst-25576	17	32	the	the	DET
ajst-25576	17	33	pid	pid	NOUN
ajst-25576	17	34	parameter	parameter	NOUN
ajst-25576	17	35	tuning	tuning	NOUN
ajst-25576	17	36	process	process	NOUN
ajst-25576	17	37	[	[	X
ajst-25576	17	38	3	3	NUM
ajst-25576	17	39	]	]	PUNCT
ajst-25576	17	40	.	.	PUNCT
ajst-25576	18	1	among	among	ADP
ajst-25576	18	2	them	they	PRON
ajst-25576	18	3	,	,	PUNCT
ajst-25576	18	4	the	the	DET
ajst-25576	18	5	beetle	beetle	NOUN
ajst-25576	18	6	antennae	antennae	NOUN
ajst-25576	18	7	search	search	NOUN
ajst-25576	18	8	(	(	PUNCT
ajst-25576	18	9	bas	bas	NOUN
ajst-25576	18	10	)	)	PUNCT
ajst-25576	18	11	algorithm	algorithm	NOUN
ajst-25576	18	12	,	,	PUNCT
ajst-25576	18	13	as	as	ADP
ajst-25576	18	14	a	a	DET
ajst-25576	18	15	new	new	ADJ
ajst-25576	18	16	bionic	bionic	ADJ
ajst-25576	18	17	optimization	optimization	NOUN
ajst-25576	18	18	algorithm	algorithm	NOUN
ajst-25576	18	19	,	,	PUNCT
ajst-25576	18	20	has	have	AUX
ajst-25576	18	21	attracted	attract	VERB
ajst-25576	18	22	wide	wide	ADJ
ajst-25576	18	23	attention	attention	NOUN
ajst-25576	18	24	for	for	ADP
ajst-25576	18	25	its	its	PRON
ajst-25576	18	26	unique	unique	ADJ
ajst-25576	18	27	search	search	NOUN
ajst-25576	18	28	mechanism	mechanism	NOUN
ajst-25576	18	29	and	and	CCONJ
ajst-25576	18	30	global	global	ADJ
ajst-25576	18	31	optimization	optimization	NOUN
ajst-25576	18	32	ability	ability	NOUN
ajst-25576	18	33	.	.	PUNCT
ajst-25576	19	1	however	however	ADV
ajst-25576	19	2	,	,	PUNCT
ajst-25576	19	3	the	the	DET
ajst-25576	19	4	traditional	traditional	ADJ
ajst-25576	19	5	bas	bas	PROPN
ajst-25576	19	6	algorithm	algorithm	NOUN
ajst-25576	19	7	still	still	ADV
ajst-25576	19	8	has	have	VERB
ajst-25576	19	9	some	some	DET
ajst-25576	19	10	limitations	limitation	NOUN
ajst-25576	19	11	in	in	ADP
ajst-25576	19	12	the	the	DET
ajst-25576	19	13	process	process	NOUN
ajst-25576	19	14	of	of	ADP
ajst-25576	19	15	optimization	optimization	NOUN
ajst-25576	19	16	,	,	PUNCT
ajst-25576	19	17	such	such	ADJ
ajst-25576	19	18	as	as	ADP
ajst-25576	19	19	easy	easy	ADJ
ajst-25576	19	20	to	to	PART
ajst-25576	19	21	fall	fall	VERB
ajst-25576	19	22	into	into	ADP
ajst-25576	19	23	local	local	ADJ
ajst-25576	19	24	optimum	optimum	ADJ
ajst-25576	19	25	and	and	CCONJ
ajst-25576	19	26	slow	slow	ADJ
ajst-25576	19	27	convergence	convergence	NOUN
ajst-25576	19	28	.	.	PUNCT
ajst-25576	20	1	to	to	PART
ajst-25576	20	2	address	address	VERB
ajst-25576	20	3	these	these	DET
ajst-25576	20	4	challenges	challenge	NOUN
ajst-25576	20	5	,	,	PUNCT
ajst-25576	20	6	this	this	DET
ajst-25576	20	7	study	study	NOUN
ajst-25576	20	8	advocates	advocate	VERB
ajst-25576	20	9	for	for	ADP
ajst-25576	20	10	a	a	DET
ajst-25576	20	11	pid	pid	NOUN
ajst-25576	20	12	parameter	parameter	NOUN
ajst-25576	20	13	tuning	tune	VERB
ajst-25576	20	14	methodology	methodology	NOUN
ajst-25576	20	15	grounded	ground	VERB
ajst-25576	20	16	in	in	ADP
ajst-25576	20	17	an	an	DET
ajst-25576	20	18	improved	improved	ADJ
ajst-25576	20	19	bas	bas	NOUN
ajst-25576	20	20	algorithm	algorithm	NOUN
ajst-25576	20	21	.	.	PUNCT
ajst-25576	21	1	through	through	ADP
ajst-25576	21	2	augmentations	augmentation	NOUN
ajst-25576	21	3	to	to	ADP
ajst-25576	21	4	the	the	DET
ajst-25576	21	5	conventional	conventional	ADJ
ajst-25576	21	6	bas	bas	PROPN
ajst-25576	21	7	algorithm	algorithm	NOUN
ajst-25576	21	8	,	,	PUNCT
ajst-25576	21	9	the	the	DET
ajst-25576	21	10	optimization	optimization	NOUN
ajst-25576	21	11	efficacy	efficacy	NOUN
ajst-25576	21	12	and	and	CCONJ
ajst-25576	21	13	convergence	convergence	NOUN
ajst-25576	21	14	velocity	velocity	NOUN
ajst-25576	21	15	of	of	ADP
ajst-25576	21	16	the	the	DET
ajst-25576	21	17	algorithm	algorithm	NOUN
ajst-25576	21	18	are	be	AUX
ajst-25576	21	19	heightened	heighten	VERB
ajst-25576	21	20	,	,	PUNCT
ajst-25576	21	21	enabling	enable	VERB
ajst-25576	21	22	a	a	DET
ajst-25576	21	23	more	more	ADV
ajst-25576	21	24	proficient	proficient	ADJ
ajst-25576	21	25	determination	determination	NOUN
ajst-25576	21	26	of	of	ADP
ajst-25576	21	27	the	the	DET
ajst-25576	21	28	optimal	optimal	ADJ
ajst-25576	21	29	parameters	parameter	NOUN
ajst-25576	21	30	for	for	ADP
ajst-25576	21	31	the	the	DET
ajst-25576	21	32	pid	pid	NOUN
ajst-25576	21	33	controller	controller	NOUN
ajst-25576	21	34	.	.	PUNCT
ajst-25576	22	1	this	this	DET
ajst-25576	22	2	investigation	investigation	NOUN
ajst-25576	22	3	holds	hold	VERB
ajst-25576	22	4	not	not	PART
ajst-25576	22	5	only	only	ADV
ajst-25576	22	6	theoretical	theoretical	ADJ
ajst-25576	22	7	significance	significance	NOUN
ajst-25576	22	8	but	but	CCONJ
ajst-25576	22	9	also	also	ADV
ajst-25576	22	10	anticipates	anticipate	VERB
ajst-25576	22	11	offering	offer	VERB
ajst-25576	22	12	novel	novel	ADJ
ajst-25576	22	13	insights	insight	NOUN
ajst-25576	22	14	and	and	CCONJ
ajst-25576	22	15	techniques	technique	NOUN
ajst-25576	22	16	for	for	ADP
ajst-25576	22	17	the	the	DET
ajst-25576	22	18	refinement	refinement	NOUN
ajst-25576	22	19	of	of	ADP
ajst-25576	22	20	industrial	industrial	ADJ
ajst-25576	22	21	control	control	NOUN
ajst-25576	22	22	systems	system	NOUN
ajst-25576	22	23	.	.	PUNCT
ajst-25576	23	1	2	2	X
ajst-25576	23	2	.	.	X
ajst-25576	23	3	introduction	introduction	NOUN
ajst-25576	23	4	of	of	ADP
ajst-25576	23	5	improved	improve	VERB
ajst-25576	23	6	bas	bas	PROPN
ajst-25576	23	7	algorithm	algorithm	NOUN
ajst-25576	23	8	bas	bas	PROPN
ajst-25576	23	9	algorithm	algorithm	PROPN
ajst-25576	23	10	is	be	AUX
ajst-25576	23	11	a	a	DET
ajst-25576	23	12	bionic	bionic	ADJ
ajst-25576	23	13	optimization	optimization	NOUN
ajst-25576	23	14	algorithm	algorithm	NOUN
ajst-25576	23	15	based	base	VERB
ajst-25576	23	16	on	on	ADP
ajst-25576	23	17	the	the	DET
ajst-25576	23	18	foraging	forage	VERB
ajst-25576	23	19	behavior	behavior	NOUN
ajst-25576	23	20	of	of	ADP
ajst-25576	23	21	longicorn	longicorn	ADJ
ajst-25576	23	22	beetles	beetle	NOUN
ajst-25576	23	23	.	.	PUNCT
ajst-25576	24	1	in	in	ADP
ajst-25576	24	2	the	the	DET
ajst-25576	24	3	process	process	NOUN
ajst-25576	24	4	of	of	ADP
ajst-25576	24	5	foraging	forage	VERB
ajst-25576	24	6	,	,	PUNCT
ajst-25576	24	7	longicorn	longicorn	VERB
ajst-25576	24	8	beetles	beetle	NOUN
ajst-25576	24	9	perceive	perceive	VERB
ajst-25576	24	10	the	the	DET
ajst-25576	24	11	odor	odor	NOUN
ajst-25576	24	12	concentration	concentration	NOUN
ajst-25576	24	13	around	around	ADP
ajst-25576	24	14	them	they	PRON
ajst-25576	24	15	through	through	ADP
ajst-25576	24	16	their	their	PRON
ajst-25576	24	17	antennae	antennae	NOUN
ajst-25576	24	18	(	(	PUNCT
ajst-25576	24	19	i.e.	i.e.	X
ajst-25576	24	20	"	"	PUNCT
ajst-25576	24	21	whiskers	whisker	NOUN
ajst-25576	24	22	"	"	PUNCT
ajst-25576	24	23	)	)	PUNCT
ajst-25576	24	24	,	,	PUNCT
ajst-25576	24	25	so	so	SCONJ
ajst-25576	24	26	as	as	SCONJ
ajst-25576	24	27	to	to	PART
ajst-25576	24	28	determine	determine	VERB
ajst-25576	24	29	the	the	DET
ajst-25576	24	30	direction	direction	NOUN
ajst-25576	24	31	of	of	ADP
ajst-25576	24	32	progress	progress	NOUN
ajst-25576	24	33	.	.	PUNCT
ajst-25576	25	1	the	the	DET
ajst-25576	25	2	algorithm	algorithm	NOUN
ajst-25576	25	3	simulates	simulate	VERB
ajst-25576	25	4	this	this	DET
ajst-25576	25	5	process	process	NOUN
ajst-25576	25	6	,	,	PUNCT
ajst-25576	25	7	and	and	CCONJ
ajst-25576	25	8	determines	determine	VERB
ajst-25576	25	9	the	the	DET
ajst-25576	25	10	search	search	NOUN
ajst-25576	25	11	direction	direction	NOUN
ajst-25576	25	12	and	and	CCONJ
ajst-25576	25	13	step	step	NOUN
ajst-25576	25	14	size	size	NOUN
ajst-25576	25	15	by	by	ADP
ajst-25576	25	16	detecting	detect	VERB
ajst-25576	25	17	the	the	DET
ajst-25576	25	18	objective	objective	ADJ
ajst-25576	25	19	function	function	NOUN
ajst-25576	25	20	value	value	NOUN
ajst-25576	25	21	in	in	ADP
ajst-25576	25	22	the	the	DET
ajst-25576	25	23	solution	solution	NOUN
ajst-25576	25	24	space	space	NOUN
ajst-25576	25	25	with	with	ADP
ajst-25576	25	26	"	"	PUNCT
ajst-25576	25	27	left	left	ADJ
ajst-25576	25	28	and	and	CCONJ
ajst-25576	25	29	right	right	ADJ
ajst-25576	25	30	whiskers	whisker	NOUN
ajst-25576	25	31	"	"	PUNCT
ajst-25576	25	32	.	.	PUNCT
ajst-25576	26	1	the	the	DET
ajst-25576	26	2	basic	basic	ADJ
ajst-25576	26	3	steps	step	NOUN
ajst-25576	26	4	of	of	ADP
ajst-25576	26	5	the	the	DET
ajst-25576	26	6	traditional	traditional	ADJ
ajst-25576	26	7	bas	bas	PROPN
ajst-25576	26	8	algorithm	algorithm	NOUN
ajst-25576	26	9	are	be	AUX
ajst-25576	26	10	as	as	SCONJ
ajst-25576	26	11	follows	follow	VERB
ajst-25576	26	12	:	:	PUNCT
ajst-25576	26	13	1	1	X
ajst-25576	26	14	.	.	X
ajst-25576	26	15	initialize	initialize	VERB
ajst-25576	26	16	the	the	DET
ajst-25576	26	17	position	position	NOUN
ajst-25576	26	18	and	and	CCONJ
ajst-25576	26	19	step	step	NOUN
ajst-25576	26	20	size	size	NOUN
ajst-25576	26	21	of	of	ADP
ajst-25576	26	22	the	the	DET
ajst-25576	26	23	longicorn	longicorn	ADJ
ajst-25576	26	24	beetle	beetle	NOUN
ajst-25576	26	25	.	.	PUNCT
ajst-25576	27	1	2	2	X
ajst-25576	27	2	.	.	X
ajst-25576	27	3	the	the	DET
ajst-25576	27	4	objective	objective	ADJ
ajst-25576	27	5	function	function	NOUN
ajst-25576	27	6	value	value	NOUN
ajst-25576	27	7	is	be	AUX
ajst-25576	27	8	detected	detect	VERB
ajst-25576	27	9	by	by	ADP
ajst-25576	27	10	the	the	DET
ajst-25576	27	11	"	"	PUNCT
ajst-25576	27	12	left	left	ADJ
ajst-25576	27	13	beard	beard	NOUN
ajst-25576	27	14	"	"	PUNCT
ajst-25576	27	15	and	and	CCONJ
ajst-25576	27	16	"	"	PUNCT
ajst-25576	27	17	right	right	ADJ
ajst-25576	27	18	beard	beard	NOUN
ajst-25576	27	19	"	"	PUNCT
ajst-25576	27	20	of	of	ADP
ajst-25576	27	21	longicorn	longicorn	ADJ
ajst-25576	27	22	beetles	beetle	NOUN
ajst-25576	27	23	.	.	PUNCT
ajst-25576	28	1	3	3	X
ajst-25576	28	2	.	.	PUNCT
ajst-25576	28	3	according	accord	VERB
ajst-25576	28	4	to	to	ADP
ajst-25576	28	5	the	the	DET
ajst-25576	28	6	difference	difference	NOUN
ajst-25576	28	7	of	of	ADP
ajst-25576	28	8	function	function	NOUN
ajst-25576	28	9	values	value	NOUN
ajst-25576	28	10	detected	detect	VERB
ajst-25576	28	11	by	by	ADP
ajst-25576	28	12	the	the	DET
ajst-25576	28	13	two	two	NUM
ajst-25576	28	14	whiskers	whisker	NOUN
ajst-25576	28	15	,	,	PUNCT
ajst-25576	28	16	the	the	DET
ajst-25576	28	17	next	next	ADJ
ajst-25576	28	18	moving	moving	NOUN
ajst-25576	28	19	direction	direction	NOUN
ajst-25576	28	20	and	and	CCONJ
ajst-25576	28	21	step	step	NOUN
ajst-25576	28	22	size	size	NOUN
ajst-25576	28	23	of	of	ADP
ajst-25576	28	24	the	the	DET
ajst-25576	28	25	longicorn	longicorn	ADJ
ajst-25576	28	26	beetle	beetle	NOUN
ajst-25576	28	27	are	be	AUX
ajst-25576	28	28	determined	determine	VERB
ajst-25576	28	29	.	.	PUNCT
ajst-25576	29	1	4	4	X
ajst-25576	29	2	.	.	X
ajst-25576	29	3	repeat	repeat	NOUN
ajst-25576	29	4	steps	step	NOUN
ajst-25576	29	5	2	2	NUM
ajst-25576	29	6	and	and	CCONJ
ajst-25576	29	7	3	3	NUM
ajst-25576	29	8	until	until	SCONJ
ajst-25576	29	9	the	the	DET
ajst-25576	29	10	stop	stop	NOUN
ajst-25576	29	11	condition	condition	NOUN
ajst-25576	29	12	is	be	AUX
ajst-25576	29	13	met	meet	VERB
ajst-25576	29	14	.	.	PUNCT
ajst-25576	30	1	the	the	DET
ajst-25576	30	2	advantage	advantage	NOUN
ajst-25576	30	3	of	of	ADP
ajst-25576	30	4	traditional	traditional	ADJ
ajst-25576	30	5	bas	bas	PROPN
ajst-25576	30	6	algorithm	algorithm	NOUN
ajst-25576	30	7	is	be	AUX
ajst-25576	30	8	that	that	SCONJ
ajst-25576	30	9	it	it	PRON
ajst-25576	30	10	is	be	AUX
ajst-25576	30	11	simple	simple	ADJ
ajst-25576	30	12	and	and	CCONJ
ajst-25576	30	13	easy	easy	ADJ
ajst-25576	30	14	to	to	PART
ajst-25576	30	15	realize	realize	VERB
ajst-25576	30	16	,	,	PUNCT
ajst-25576	30	17	and	and	CCONJ
ajst-25576	30	18	it	it	PRON
ajst-25576	30	19	does	do	AUX
ajst-25576	30	20	not	not	PART
ajst-25576	30	21	need	need	VERB
ajst-25576	30	22	gradient	gradient	ADJ
ajst-25576	30	23	information	information	NOUN
ajst-25576	30	24	of	of	ADP
ajst-25576	30	25	objective	objective	ADJ
ajst-25576	30	26	function	function	NOUN
ajst-25576	30	27	,	,	PUNCT
ajst-25576	30	28	so	so	CCONJ
ajst-25576	30	29	it	it	PRON
ajst-25576	30	30	is	be	AUX
ajst-25576	30	31	suitable	suitable	ADJ
ajst-25576	30	32	for	for	ADP
ajst-25576	30	33	nonconvex	nonconvex	NOUN
ajst-25576	30	34	and	and	CCONJ
ajst-25576	30	35	nonlinear	nonlinear	ADJ
ajst-25576	30	36	optimization	optimization	NOUN
ajst-25576	30	37	problems	problem	NOUN
ajst-25576	30	38	and	and	CCONJ
ajst-25576	30	39	has	have	VERB
ajst-25576	30	40	a	a	DET
ajst-25576	30	41	certain	certain	ADJ
ajst-25576	30	42	global	global	ADJ
ajst-25576	30	43	search	search	NOUN
ajst-25576	30	44	ability	ability	NOUN
ajst-25576	30	45	.	.	PUNCT
ajst-25576	31	1	however	however	ADV
ajst-25576	31	2	,	,	PUNCT
ajst-25576	31	3	the	the	DET
ajst-25576	31	4	algorithm	algorithm	NOUN
ajst-25576	31	5	also	also	ADV
ajst-25576	31	6	has	have	VERB
ajst-25576	31	7	some	some	DET
ajst-25576	31	8	shortcomings	shortcoming	NOUN
ajst-25576	31	9	,	,	PUNCT
ajst-25576	31	10	such	such	ADJ
ajst-25576	31	11	as	as	ADP
ajst-25576	31	12	easy	easy	ADJ
ajst-25576	31	13	to	to	PART
ajst-25576	31	14	fall	fall	VERB
ajst-25576	31	15	into	into	ADP
ajst-25576	31	16	local	local	ADJ
ajst-25576	31	17	optimal	optimal	ADJ
ajst-25576	31	18	solution	solution	NOUN
ajst-25576	31	19	,	,	PUNCT
ajst-25576	31	20	limited	limited	ADJ
ajst-25576	31	21	global	global	ADJ
ajst-25576	31	22	optimization	optimization	NOUN
ajst-25576	31	23	ability	ability	NOUN
ajst-25576	31	24	and	and	CCONJ
ajst-25576	31	25	slow	slow	ADJ
ajst-25576	31	26	convergence	convergence	NOUN
ajst-25576	31	27	speed	speed	NOUN
ajst-25576	31	28	,	,	PUNCT
ajst-25576	31	29	especially	especially	ADV
ajst-25576	31	30	when	when	SCONJ
ajst-25576	31	31	it	it	PRON
ajst-25576	31	32	is	be	AUX
ajst-25576	31	33	close	close	ADJ
ajst-25576	31	34	to	to	ADP
ajst-25576	31	35	the	the	DET
ajst-25576	31	36	optimal	optimal	ADJ
ajst-25576	31	37	solution	solution	NOUN
ajst-25576	31	38	,	,	PUNCT
ajst-25576	31	39	the	the	DET
ajst-25576	31	40	search	search	NOUN
ajst-25576	31	41	efficiency	efficiency	NOUN
ajst-25576	31	42	will	will	AUX
ajst-25576	31	43	decrease	decrease	VERB
ajst-25576	31	44	,	,	PUNCT
ajst-25576	31	45	and	and	CCONJ
ajst-25576	31	46	the	the	DET
ajst-25576	31	47	choice	choice	NOUN
ajst-25576	31	48	of	of	ADP
ajst-25576	31	49	step	step	NOUN
ajst-25576	31	50	size	size	NOUN
ajst-25576	31	51	has	have	VERB
ajst-25576	31	52	a	a	DET
ajst-25576	31	53	great	great	ADJ
ajst-25576	31	54	influence	influence	NOUN
ajst-25576	31	55	on	on	ADP
ajst-25576	31	56	the	the	DET
ajst-25576	31	57	performance	performance	NOUN
ajst-25576	31	58	of	of	ADP
ajst-25576	31	59	the	the	DET
ajst-25576	31	60	algorithm	algorithm	NOUN
ajst-25576	31	61	,	,	PUNCT
ajst-25576	31	62	so	so	SCONJ
ajst-25576	31	63	it	it	PRON
ajst-25576	31	64	is	be	AUX
ajst-25576	31	65	difficult	difficult	ADJ
ajst-25576	31	66	to	to	PART
ajst-25576	31	67	determine	determine	VERB
ajst-25576	31	68	the	the	DET
ajst-25576	31	69	appropriate	appropriate	ADJ
ajst-25576	31	70	step	step	NOUN
ajst-25576	31	71	size	size	NOUN
ajst-25576	31	72	.	.	PUNCT
ajst-25576	32	1	aiming	aim	VERB
ajst-25576	32	2	at	at	ADP
ajst-25576	32	3	the	the	DET
ajst-25576	32	4	shortcomings	shortcoming	NOUN
ajst-25576	32	5	of	of	ADP
ajst-25576	32	6	traditional	traditional	ADJ
ajst-25576	32	7	bas	bas	PROPN
ajst-25576	32	8	algorithm	algorithm	NOUN
ajst-25576	32	9	,	,	PUNCT
ajst-25576	32	10	73	73	NUM
ajst-25576	32	11	an	an	DET
ajst-25576	32	12	improved	improved	ADJ
ajst-25576	32	13	bas	bas	PROPN
ajst-25576	32	14	algorithm	algorithm	NOUN
ajst-25576	32	15	is	be	AUX
ajst-25576	32	16	designed	design	VERB
ajst-25576	32	17	in	in	ADP
ajst-25576	32	18	this	this	DET
ajst-25576	32	19	study	study	NOUN
ajst-25576	32	20	.	.	PUNCT
ajst-25576	33	1	while	while	SCONJ
ajst-25576	33	2	maintaining	maintain	VERB
ajst-25576	33	3	the	the	DET
ajst-25576	33	4	simplicity	simplicity	NOUN
ajst-25576	33	5	of	of	ADP
ajst-25576	33	6	traditional	traditional	ADJ
ajst-25576	33	7	bas	bas	PROPN
ajst-25576	33	8	algorithm	algorithm	NOUN
ajst-25576	33	9	,	,	PUNCT
ajst-25576	33	10	this	this	DET
ajst-25576	33	11	algorithm	algorithm	NOUN
ajst-25576	33	12	improves	improve	VERB
ajst-25576	33	13	the	the	DET
ajst-25576	33	14	global	global	ADJ
ajst-25576	33	15	optimization	optimization	NOUN
ajst-25576	33	16	ability	ability	NOUN
ajst-25576	33	17	and	and	CCONJ
ajst-25576	33	18	convergence	convergence	NOUN
ajst-25576	33	19	speed	speed	NOUN
ajst-25576	33	20	[	[	X
ajst-25576	33	21	4	4	NUM
ajst-25576	33	22	-	-	SYM
ajst-25576	33	23	5	5	NUM
ajst-25576	33	24	]	]	PUNCT
ajst-25576	33	25	.	.	PUNCT
ajst-25576	34	1	the	the	DET
ajst-25576	34	2	algorithm	algorithm	NOUN
ajst-25576	34	3	is	be	AUX
ajst-25576	34	4	more	more	ADV
ajst-25576	34	5	flexible	flexible	ADJ
ajst-25576	34	6	and	and	CCONJ
ajst-25576	34	7	efficient	efficient	ADJ
ajst-25576	34	8	by	by	ADP
ajst-25576	34	9	dynamically	dynamically	ADV
ajst-25576	34	10	adjusting	adjust	VERB
ajst-25576	34	11	the	the	DET
ajst-25576	34	12	step	step	NOUN
ajst-25576	34	13	size	size	NOUN
ajst-25576	34	14	,	,	PUNCT
ajst-25576	34	15	introducing	introduce	VERB
ajst-25576	34	16	random	random	ADJ
ajst-25576	34	17	disturbance	disturbance	NOUN
ajst-25576	34	18	and	and	CCONJ
ajst-25576	34	19	elite	elite	ADJ
ajst-25576	34	20	retention	retention	NOUN
ajst-25576	34	21	strategy	strategy	NOUN
ajst-25576	34	22	.	.	PUNCT
ajst-25576	35	1	dynamically	dynamically	ADV
ajst-25576	35	2	adjust	adjust	VERB
ajst-25576	35	3	the	the	DET
ajst-25576	35	4	step	step	NOUN
ajst-25576	35	5	size	size	NOUN
ajst-25576	35	6	according	accord	VERB
ajst-25576	35	7	to	to	ADP
ajst-25576	35	8	the	the	DET
ajst-25576	35	9	search	search	NOUN
ajst-25576	35	10	situation	situation	NOUN
ajst-25576	35	11	in	in	ADP
ajst-25576	35	12	the	the	DET
ajst-25576	35	13	iterative	iterative	NOUN
ajst-25576	35	14	process	process	NOUN
ajst-25576	35	15	[	[	X
ajst-25576	35	16	6	6	NUM
ajst-25576	35	17	]	]	PUNCT
ajst-25576	35	18	.	.	PUNCT
ajst-25576	36	1	in	in	ADP
ajst-25576	36	2	the	the	DET
ajst-25576	36	3	initial	initial	ADJ
ajst-25576	36	4	stage	stage	NOUN
ajst-25576	36	5	of	of	ADP
ajst-25576	36	6	search	search	NOUN
ajst-25576	36	7	,	,	PUNCT
ajst-25576	36	8	a	a	DET
ajst-25576	36	9	larger	large	ADJ
ajst-25576	36	10	step	step	NOUN
ajst-25576	36	11	size	size	NOUN
ajst-25576	36	12	is	be	AUX
ajst-25576	36	13	adopted	adopt	VERB
ajst-25576	36	14	to	to	PART
ajst-25576	36	15	speed	speed	VERB
ajst-25576	36	16	up	up	ADP
ajst-25576	36	17	the	the	DET
ajst-25576	36	18	global	global	ADJ
ajst-25576	36	19	search	search	NOUN
ajst-25576	36	20	;	;	PUNCT
ajst-25576	36	21	with	with	ADP
ajst-25576	36	22	the	the	DET
ajst-25576	36	23	iteration	iteration	NOUN
ajst-25576	36	24	,	,	PUNCT
ajst-25576	36	25	the	the	DET
ajst-25576	36	26	step	step	NOUN
ajst-25576	36	27	size	size	NOUN
ajst-25576	36	28	is	be	AUX
ajst-25576	36	29	gradually	gradually	ADV
ajst-25576	36	30	reduced	reduce	VERB
ajst-25576	36	31	to	to	PART
ajst-25576	36	32	improve	improve	VERB
ajst-25576	36	33	the	the	DET
ajst-25576	36	34	accuracy	accuracy	NOUN
ajst-25576	36	35	of	of	ADP
ajst-25576	36	36	local	local	ADJ
ajst-25576	36	37	search	search	NOUN
ajst-25576	36	38	.	.	PUNCT
ajst-25576	37	1	step	step	NOUN
ajst-25576	37	2	adjustment	adjustment	NOUN
ajst-25576	37	3	formula	formula	NOUN
ajst-25576	37	4	:	:	PUNCT
ajst-25576	37	5	t	t	PROPN
ajst-25576	37	6	tt	tt	PROPN
ajst-25576	37	7	ss	ss	PROPN
ajst-25576	37	8	1	1	PROPN
ajst-25576	37	9	(	(	PUNCT
ajst-25576	37	10	1	1	NUM
ajst-25576	37	11	)	)	PUNCT
ajst-25576	37	12	where	where	SCONJ
ajst-25576	37	13	ts	ts	ADV
ajst-25576	37	14	is	be	AUX
ajst-25576	37	15	the	the	DET
ajst-25576	37	16	step	step	NOUN
ajst-25576	37	17	size	size	NOUN
ajst-25576	37	18	of	of	ADP
ajst-25576	37	19	t	t	NOUN
ajst-25576	37	20	generation	generation	NOUN
ajst-25576	37	21	and	and	CCONJ
ajst-25576	37	22			NOUN
ajst-25576	37	23	is	be	AUX
ajst-25576	37	24	the	the	DET
ajst-25576	37	25	step	step	NOUN
ajst-25576	37	26	size	size	NOUN
ajst-25576	37	27	attenuation	attenuation	NOUN
ajst-25576	37	28	factor	factor	NOUN
ajst-25576	37	29	(	(	PUNCT
ajst-25576	37	30	10	10	NUM
ajst-25576	37	31			NUM
ajst-25576	37	32	)	)	PUNCT
ajst-25576	37	33	.	.	PUNCT
ajst-25576	38	1	in	in	ADP
ajst-25576	38	2	order	order	NOUN
ajst-25576	38	3	to	to	PART
ajst-25576	38	4	enhance	enhance	VERB
ajst-25576	38	5	the	the	DET
ajst-25576	38	6	global	global	ADJ
ajst-25576	38	7	search	search	NOUN
ajst-25576	38	8	ability	ability	NOUN
ajst-25576	38	9	of	of	ADP
ajst-25576	38	10	the	the	DET
ajst-25576	38	11	algorithm	algorithm	NOUN
ajst-25576	38	12	and	and	CCONJ
ajst-25576	38	13	avoid	avoid	VERB
ajst-25576	38	14	falling	fall	VERB
ajst-25576	38	15	into	into	ADP
ajst-25576	38	16	local	local	ADJ
ajst-25576	38	17	optimum	optimum	NOUN
ajst-25576	38	18	,	,	PUNCT
ajst-25576	38	19	when	when	SCONJ
ajst-25576	38	20	the	the	DET
ajst-25576	38	21	algorithm	algorithm	NOUN
ajst-25576	38	22	has	have	AUX
ajst-25576	38	23	not	not	PART
ajst-25576	38	24	been	be	AUX
ajst-25576	38	25	improved	improve	VERB
ajst-25576	38	26	obviously	obviously	ADV
ajst-25576	38	27	for	for	ADP
ajst-25576	38	28	many	many	ADJ
ajst-25576	38	29	iterations	iteration	NOUN
ajst-25576	38	30	,	,	PUNCT
ajst-25576	38	31	random	random	ADJ
ajst-25576	38	32	disturbance	disturbance	NOUN
ajst-25576	38	33	is	be	AUX
ajst-25576	38	34	applied	apply	VERB
ajst-25576	38	35	to	to	ADP
ajst-25576	38	36	the	the	DET
ajst-25576	38	37	position	position	NOUN
ajst-25576	38	38	of	of	ADP
ajst-25576	38	39	the	the	DET
ajst-25576	38	40	longicorn	longicorn	ADJ
ajst-25576	38	41	beetle	beetle	NOUN
ajst-25576	38	42	.	.	PUNCT
ajst-25576	39	1	disturbance	disturbance	NOUN
ajst-25576	39	2	formula	formula	NOUN
ajst-25576	39	3	:	:	PUNCT
ajst-25576	40	1			PROPN
ajst-25576	40	2	randβxx	randβxx	PUNCT
ajst-25576	41	1	tt	tt	PROPN
ajst-25576	41	2	1	1	PROPN
ajst-25576	41	3	(	(	PUNCT
ajst-25576	41	4	2	2	X
ajst-25576	41	5	)	)	PUNCT
ajst-25576	41	6	where	where	SCONJ
ajst-25576	41	7	tx	tx	PROPN
ajst-25576	41	8	is	be	AUX
ajst-25576	41	9	the	the	DET
ajst-25576	41	10	position	position	NOUN
ajst-25576	41	11	of	of	ADP
ajst-25576	41	12	the	the	DET
ajst-25576	41	13	t	t	NOUN
ajst-25576	41	14	generation	generation	NOUN
ajst-25576	41	15	longicorn	longicorn	VERB
ajst-25576	41	16	beetle	beetle	NOUN
ajst-25576	41	17	,	,	PUNCT
ajst-25576	41	18	β	β	X
ajst-25576	41	19	is	be	AUX
ajst-25576	41	20	the	the	DET
ajst-25576	41	21	disturbance	disturbance	NOUN
ajst-25576	41	22	coefficient	coefficient	NOUN
ajst-25576	41	23	,	,	PUNCT
ajst-25576	41	24	and	and	CCONJ
ajst-25576	41	25			PROPN
ajst-25576	42	1	rand	rand	PROPN
ajst-25576	42	2	generates	generate	VERB
ajst-25576	42	3	a	a	DET
ajst-25576	42	4	random	random	ADJ
ajst-25576	42	5	number	number	NOUN
ajst-25576	42	6	.	.	PUNCT
ajst-25576	43	1	in	in	ADP
ajst-25576	43	2	the	the	DET
ajst-25576	43	3	iterative	iterative	NOUN
ajst-25576	43	4	process	process	NOUN
ajst-25576	43	5	,	,	PUNCT
ajst-25576	43	6	the	the	DET
ajst-25576	43	7	historical	historical	ADJ
ajst-25576	43	8	optimal	optimal	ADJ
ajst-25576	43	9	solution	solution	NOUN
ajst-25576	43	10	is	be	AUX
ajst-25576	43	11	retained	retain	VERB
ajst-25576	43	12	and	and	CCONJ
ajst-25576	43	13	used	use	VERB
ajst-25576	43	14	as	as	ADP
ajst-25576	43	15	a	a	DET
ajst-25576	43	16	reference	reference	NOUN
ajst-25576	43	17	point	point	NOUN
ajst-25576	43	18	to	to	PART
ajst-25576	43	19	guide	guide	VERB
ajst-25576	43	20	the	the	DET
ajst-25576	43	21	longicorn	longicorn	ADJ
ajst-25576	43	22	beetle	beetle	NOUN
ajst-25576	43	23	to	to	PART
ajst-25576	43	24	search	search	VERB
ajst-25576	43	25	in	in	ADP
ajst-25576	43	26	a	a	DET
ajst-25576	43	27	better	well	ADJ
ajst-25576	43	28	direction	direction	NOUN
ajst-25576	43	29	.	.	PUNCT
ajst-25576	44	1	3	3	X
ajst-25576	44	2	.	.	X
ajst-25576	44	3	pid	pid	NOUN
ajst-25576	44	4	parameter	parameter	NOUN
ajst-25576	44	5	tuning	tuning	NOUN
ajst-25576	44	6	method	method	NOUN
ajst-25576	44	7	based	base	VERB
ajst-25576	44	8	on	on	ADP
ajst-25576	44	9	improved	improve	VERB
ajst-25576	44	10	bas	bas	PROPN
ajst-25576	44	11	algorithm	algorithm	NOUN
ajst-25576	44	12	the	the	DET
ajst-25576	44	13	improved	improved	ADJ
ajst-25576	44	14	bas	bas	PROPN
ajst-25576	44	15	algorithm	algorithm	NOUN
ajst-25576	44	16	is	be	AUX
ajst-25576	44	17	applied	apply	VERB
ajst-25576	44	18	to	to	ADP
ajst-25576	44	19	the	the	DET
ajst-25576	44	20	parameter	parameter	NOUN
ajst-25576	44	21	tuning	tuning	NOUN
ajst-25576	44	22	of	of	ADP
ajst-25576	44	23	pid	pid	NOUN
ajst-25576	44	24	controller	controller	NOUN
ajst-25576	44	25	to	to	PART
ajst-25576	44	26	optimize	optimize	VERB
ajst-25576	44	27	the	the	DET
ajst-25576	44	28	performance	performance	NOUN
ajst-25576	44	29	of	of	ADP
ajst-25576	44	30	the	the	DET
ajst-25576	44	31	controller	controller	NOUN
ajst-25576	44	32	.	.	PUNCT
ajst-25576	45	1	by	by	ADP
ajst-25576	45	2	combining	combine	VERB
ajst-25576	45	3	dynamic	dynamic	ADJ
ajst-25576	45	4	step	step	NOUN
ajst-25576	45	5	adjustment	adjustment	NOUN
ajst-25576	45	6	,	,	PUNCT
ajst-25576	45	7	random	random	ADJ
ajst-25576	45	8	disturbance	disturbance	NOUN
ajst-25576	45	9	and	and	CCONJ
ajst-25576	45	10	elite	elite	ADJ
ajst-25576	45	11	retention	retention	NOUN
ajst-25576	45	12	strategy	strategy	NOUN
ajst-25576	45	13	,	,	PUNCT
ajst-25576	45	14	the	the	DET
ajst-25576	45	15	improved	improve	VERB
ajst-25576	45	16	bas	bas	PROPN
ajst-25576	45	17	algorithm	algorithm	NOUN
ajst-25576	45	18	not	not	PART
ajst-25576	45	19	only	only	ADV
ajst-25576	45	20	retains	retain	VERB
ajst-25576	45	21	the	the	DET
ajst-25576	45	22	simplicity	simplicity	NOUN
ajst-25576	45	23	of	of	ADP
ajst-25576	45	24	the	the	DET
ajst-25576	45	25	traditional	traditional	ADJ
ajst-25576	45	26	algorithm	algorithm	NOUN
ajst-25576	45	27	,	,	PUNCT
ajst-25576	45	28	but	but	CCONJ
ajst-25576	45	29	also	also	ADV
ajst-25576	45	30	significantly	significantly	ADV
ajst-25576	45	31	improves	improve	VERB
ajst-25576	45	32	the	the	DET
ajst-25576	45	33	global	global	ADJ
ajst-25576	45	34	optimization	optimization	NOUN
ajst-25576	45	35	ability	ability	NOUN
ajst-25576	45	36	and	and	CCONJ
ajst-25576	45	37	convergence	convergence	NOUN
ajst-25576	45	38	speed	speed	NOUN
ajst-25576	45	39	,	,	PUNCT
ajst-25576	45	40	making	make	VERB
ajst-25576	45	41	it	it	PRON
ajst-25576	45	42	more	more	ADV
ajst-25576	45	43	suitable	suitable	ADJ
ajst-25576	45	44	for	for	ADP
ajst-25576	45	45	pid	pid	NOUN
ajst-25576	45	46	parameter	parameter	NOUN
ajst-25576	45	47	optimization	optimization	NOUN
ajst-25576	45	48	[	[	X
ajst-25576	45	49	7	7	NUM
ajst-25576	45	50	-	-	SYM
ajst-25576	45	51	8	8	NUM
ajst-25576	45	52	]	]	PUNCT
ajst-25576	45	53	.	.	PUNCT
ajst-25576	46	1	an	an	DET
ajst-25576	46	2	objective	objective	ADJ
ajst-25576	46	3	function	function	NOUN
ajst-25576	46	4	is	be	AUX
ajst-25576	46	5	defined	define	VERB
ajst-25576	46	6	,	,	PUNCT
ajst-25576	46	7	which	which	PRON
ajst-25576	46	8	comprehensively	comprehensively	ADV
ajst-25576	46	9	considers	consider	VERB
ajst-25576	46	10	the	the	DET
ajst-25576	46	11	performance	performance	NOUN
ajst-25576	46	12	indexes	index	NOUN
ajst-25576	46	13	such	such	ADJ
ajst-25576	46	14	as	as	ADP
ajst-25576	46	15	overshoot	overshoot	NOUN
ajst-25576	46	16	,	,	PUNCT
ajst-25576	46	17	regulation	regulation	NOUN
ajst-25576	46	18	time	time	NOUN
ajst-25576	46	19	and	and	CCONJ
ajst-25576	46	20	steady	steady	ADJ
ajst-25576	46	21	-	-	PUNCT
ajst-25576	46	22	state	state	NOUN
ajst-25576	46	23	error	error	NOUN
ajst-25576	46	24	of	of	ADP
ajst-25576	46	25	the	the	DET
ajst-25576	46	26	system	system	NOUN
ajst-25576	46	27	.	.	PUNCT
ajst-25576	47	1	eerrorsteadystatωmesettlingtiωovershootωj	eerrorsteadystatωmesettlingtiωovershootωj	PROPN
ajst-25576	47	2	321	321	NUM
ajst-25576	47	3			NOUN
ajst-25576	47	4	(	(	PUNCT
ajst-25576	47	5	3	3	NUM
ajst-25576	47	6	)	)	PUNCT
ajst-25576	47	7	among	among	ADP
ajst-25576	47	8	them	they	PRON
ajst-25576	47	9	,	,	PUNCT
ajst-25576	47	10	321	321	NUM
ajst-25576	47	11	ωωω	ωωω	NOUN
ajst-25576	47	12	,	,	PUNCT
ajst-25576	47	13	,	,	PUNCT
ajst-25576	47	14	is	be	AUX
ajst-25576	47	15	the	the	DET
ajst-25576	47	16	weight	weight	NOUN
ajst-25576	47	17	coefficient	coefficient	NOUN
ajst-25576	47	18	,	,	PUNCT
ajst-25576	47	19	which	which	PRON
ajst-25576	47	20	is	be	AUX
ajst-25576	47	21	used	use	VERB
ajst-25576	47	22	to	to	PART
ajst-25576	47	23	balance	balance	VERB
ajst-25576	47	24	the	the	DET
ajst-25576	47	25	importance	importance	NOUN
ajst-25576	47	26	of	of	ADP
ajst-25576	47	27	different	different	ADJ
ajst-25576	47	28	performance	performance	NOUN
ajst-25576	47	29	indicators	indicator	NOUN
ajst-25576	47	30	.	.	PUNCT
ajst-25576	48	1	eerrorsteadystatmesettlingtiovershoot	eerrorsteadystatmesettlingtiovershoot	PROPN
ajst-25576	48	2	,	,	PUNCT
ajst-25576	48	3	,	,	PUNCT
ajst-25576	48	4	represents	represent	VERB
ajst-25576	48	5	the	the	DET
ajst-25576	48	6	maximum	maximum	ADJ
ajst-25576	48	7	overshoot	overshoot	NOUN
ajst-25576	48	8	of	of	ADP
ajst-25576	48	9	the	the	DET
ajst-25576	48	10	system	system	NOUN
ajst-25576	48	11	,	,	PUNCT
ajst-25576	48	12	the	the	DET
ajst-25576	48	13	time	time	NOUN
ajst-25576	48	14	required	require	VERB
ajst-25576	48	15	to	to	PART
ajst-25576	48	16	reach	reach	VERB
ajst-25576	48	17	the	the	DET
ajst-25576	48	18	steady	steady	ADJ
ajst-25576	48	19	state	state	NOUN
ajst-25576	48	20	and	and	CCONJ
ajst-25576	48	21	the	the	DET
ajst-25576	48	22	error	error	NOUN
ajst-25576	48	23	in	in	ADP
ajst-25576	48	24	the	the	DET
ajst-25576	48	25	steady	steady	ADJ
ajst-25576	48	26	state	state	NOUN
ajst-25576	48	27	respectively	respectively	ADV
ajst-25576	48	28	.	.	PUNCT
ajst-25576	49	1	the	the	DET
ajst-25576	49	2	improved	improved	ADJ
ajst-25576	49	3	bas	bas	PROPN
ajst-25576	49	4	algorithm	algorithm	NOUN
ajst-25576	49	5	is	be	AUX
ajst-25576	49	6	used	use	VERB
ajst-25576	49	7	for	for	ADP
ajst-25576	49	8	iterative	iterative	ADJ
ajst-25576	49	9	search	search	NOUN
ajst-25576	49	10	.	.	PUNCT
ajst-25576	50	1	in	in	ADP
ajst-25576	50	2	each	each	DET
ajst-25576	50	3	iteration	iteration	NOUN
ajst-25576	50	4	,	,	PUNCT
ajst-25576	50	5	the	the	DET
ajst-25576	50	6	value	value	NOUN
ajst-25576	50	7	of	of	ADP
ajst-25576	50	8	the	the	DET
ajst-25576	50	9	objective	objective	ADJ
ajst-25576	50	10	function	function	NOUN
ajst-25576	50	11	is	be	AUX
ajst-25576	50	12	calculated	calculate	VERB
ajst-25576	50	13	according	accord	VERB
ajst-25576	50	14	to	to	ADP
ajst-25576	50	15	the	the	DET
ajst-25576	50	16	combination	combination	NOUN
ajst-25576	50	17	of	of	ADP
ajst-25576	50	18	pid	pid	NOUN
ajst-25576	50	19	parameters	parameter	NOUN
ajst-25576	50	20	corresponding	correspond	VERB
ajst-25576	50	21	to	to	ADP
ajst-25576	50	22	the	the	DET
ajst-25576	50	23	"	"	PUNCT
ajst-25576	50	24	left	left	ADJ
ajst-25576	50	25	beard	beard	NOUN
ajst-25576	50	26	"	"	PUNCT
ajst-25576	50	27	and	and	CCONJ
ajst-25576	50	28	"	"	PUNCT
ajst-25576	50	29	right	right	ADJ
ajst-25576	50	30	beard	beard	NOUN
ajst-25576	50	31	"	"	PUNCT
ajst-25576	50	32	of	of	ADP
ajst-25576	50	33	longicorn	longicorn	ADJ
ajst-25576	50	34	beetles	beetle	NOUN
ajst-25576	50	35	.	.	PUNCT
ajst-25576	51	1	according	accord	VERB
ajst-25576	51	2	to	to	ADP
ajst-25576	51	3	the	the	DET
ajst-25576	51	4	difference	difference	NOUN
ajst-25576	51	5	of	of	ADP
ajst-25576	51	6	the	the	DET
ajst-25576	51	7	objective	objective	ADJ
ajst-25576	51	8	function	function	NOUN
ajst-25576	51	9	values	value	NOUN
ajst-25576	51	10	detected	detect	VERB
ajst-25576	51	11	by	by	ADP
ajst-25576	51	12	the	the	DET
ajst-25576	51	13	two	two	NUM
ajst-25576	51	14	sensors	sensor	NOUN
ajst-25576	51	15	,	,	PUNCT
ajst-25576	51	16	the	the	DET
ajst-25576	51	17	next	next	ADJ
ajst-25576	51	18	moving	moving	NOUN
ajst-25576	51	19	direction	direction	NOUN
ajst-25576	51	20	and	and	CCONJ
ajst-25576	51	21	step	step	NOUN
ajst-25576	51	22	size	size	NOUN
ajst-25576	51	23	of	of	ADP
ajst-25576	51	24	the	the	DET
ajst-25576	51	25	longicorn	longicorn	ADJ
ajst-25576	51	26	beetle	beetle	NOUN
ajst-25576	51	27	(	(	PUNCT
ajst-25576	51	28	pid	pid	NOUN
ajst-25576	51	29	parameters	parameter	NOUN
ajst-25576	51	30	)	)	PUNCT
ajst-25576	51	31	are	be	AUX
ajst-25576	51	32	determined	determine	VERB
ajst-25576	51	33	.	.	PUNCT
ajst-25576	52	1	the	the	DET
ajst-25576	52	2	dynamic	dynamic	ADJ
ajst-25576	52	3	step	step	NOUN
ajst-25576	52	4	size	size	NOUN
ajst-25576	52	5	adjustment	adjustment	NOUN
ajst-25576	52	6	strategy	strategy	NOUN
ajst-25576	52	7	is	be	AUX
ajst-25576	52	8	applied	apply	VERB
ajst-25576	52	9	to	to	PART
ajst-25576	52	10	gradually	gradually	ADV
ajst-25576	52	11	reduce	reduce	VERB
ajst-25576	52	12	the	the	DET
ajst-25576	52	13	step	step	NOUN
ajst-25576	52	14	size	size	NOUN
ajst-25576	52	15	with	with	ADP
ajst-25576	52	16	the	the	DET
ajst-25576	52	17	iteration	iteration	NOUN
ajst-25576	52	18	to	to	PART
ajst-25576	52	19	improve	improve	VERB
ajst-25576	52	20	the	the	DET
ajst-25576	52	21	search	search	NOUN
ajst-25576	52	22	accuracy	accuracy	NOUN
ajst-25576	52	23	.	.	PUNCT
ajst-25576	53	1	if	if	SCONJ
ajst-25576	53	2	the	the	DET
ajst-25576	53	3	objective	objective	ADJ
ajst-25576	53	4	function	function	NOUN
ajst-25576	53	5	value	value	NOUN
ajst-25576	53	6	of	of	ADP
ajst-25576	53	7	the	the	DET
ajst-25576	53	8	algorithm	algorithm	NOUN
ajst-25576	53	9	has	have	AUX
ajst-25576	53	10	not	not	PART
ajst-25576	53	11	improved	improve	VERB
ajst-25576	53	12	obviously	obviously	ADV
ajst-25576	53	13	after	after	ADP
ajst-25576	53	14	repeated	repeat	VERB
ajst-25576	53	15	iterations	iteration	NOUN
ajst-25576	53	16	,	,	PUNCT
ajst-25576	53	17	random	random	ADJ
ajst-25576	53	18	disturbance	disturbance	NOUN
ajst-25576	53	19	is	be	AUX
ajst-25576	53	20	applied	apply	VERB
ajst-25576	53	21	to	to	ADP
ajst-25576	53	22	the	the	DET
ajst-25576	53	23	position	position	NOUN
ajst-25576	53	24	of	of	ADP
ajst-25576	53	25	the	the	DET
ajst-25576	53	26	longicorn	longicorn	ADJ
ajst-25576	53	27	beetle	beetle	NOUN
ajst-25576	53	28	to	to	PART
ajst-25576	53	29	enhance	enhance	VERB
ajst-25576	53	30	the	the	DET
ajst-25576	53	31	global	global	ADJ
ajst-25576	53	32	search	search	NOUN
ajst-25576	53	33	ability	ability	NOUN
ajst-25576	53	34	.	.	PUNCT
ajst-25576	54	1	in	in	ADP
ajst-25576	54	2	the	the	DET
ajst-25576	54	3	iterative	iterative	NOUN
ajst-25576	54	4	process	process	NOUN
ajst-25576	54	5	,	,	PUNCT
ajst-25576	54	6	the	the	DET
ajst-25576	54	7	historical	historical	ADJ
ajst-25576	54	8	optimal	optimal	ADJ
ajst-25576	54	9	solution	solution	NOUN
ajst-25576	54	10	(	(	PUNCT
ajst-25576	54	11	that	that	PRON
ajst-25576	54	12	is	is	ADV
ajst-25576	54	13	,	,	PUNCT
ajst-25576	54	14	the	the	DET
ajst-25576	54	15	pid	pid	NOUN
ajst-25576	54	16	parameter	parameter	NOUN
ajst-25576	54	17	combination	combination	NOUN
ajst-25576	54	18	with	with	ADP
ajst-25576	54	19	the	the	DET
ajst-25576	54	20	minimum	minimum	ADJ
ajst-25576	54	21	objective	objective	ADJ
ajst-25576	54	22	function	function	NOUN
ajst-25576	54	23	value	value	NOUN
ajst-25576	54	24	)	)	PUNCT
ajst-25576	54	25	is	be	AUX
ajst-25576	54	26	recorded	record	VERB
ajst-25576	54	27	and	and	CCONJ
ajst-25576	54	28	retained	retain	VERB
ajst-25576	54	29	.	.	PUNCT
ajst-25576	55	1	using	use	VERB
ajst-25576	55	2	the	the	DET
ajst-25576	55	3	elite	elite	ADJ
ajst-25576	55	4	retention	retention	NOUN
ajst-25576	55	5	strategy	strategy	NOUN
ajst-25576	55	6	,	,	PUNCT
ajst-25576	55	7	the	the	DET
ajst-25576	55	8	historical	historical	ADJ
ajst-25576	55	9	optimal	optimal	ADJ
ajst-25576	55	10	solution	solution	NOUN
ajst-25576	55	11	is	be	AUX
ajst-25576	55	12	taken	take	VERB
ajst-25576	55	13	as	as	SCONJ
ajst-25576	55	14	the	the	DET
ajst-25576	55	15	reference	reference	NOUN
ajst-25576	55	16	point	point	NOUN
ajst-25576	55	17	to	to	PART
ajst-25576	55	18	guide	guide	VERB
ajst-25576	55	19	the	the	DET
ajst-25576	55	20	longicorn	longicorn	ADJ
ajst-25576	55	21	beetle	beetle	NOUN
ajst-25576	55	22	to	to	PART
ajst-25576	55	23	search	search	VERB
ajst-25576	55	24	in	in	ADP
ajst-25576	55	25	a	a	DET
ajst-25576	55	26	better	well	ADJ
ajst-25576	55	27	direction	direction	NOUN
ajst-25576	55	28	.	.	PUNCT
ajst-25576	56	1	when	when	SCONJ
ajst-25576	56	2	the	the	DET
ajst-25576	56	3	maximum	maximum	ADJ
ajst-25576	56	4	number	number	NOUN
ajst-25576	56	5	of	of	ADP
ajst-25576	56	6	iterations	iteration	NOUN
ajst-25576	56	7	is	be	AUX
ajst-25576	56	8	reached	reach	VERB
ajst-25576	56	9	or	or	CCONJ
ajst-25576	56	10	a	a	DET
ajst-25576	56	11	solution	solution	NOUN
ajst-25576	56	12	satisfying	satisfy	VERB
ajst-25576	56	13	the	the	DET
ajst-25576	56	14	accuracy	accuracy	NOUN
ajst-25576	56	15	requirement	requirement	NOUN
ajst-25576	56	16	is	be	AUX
ajst-25576	56	17	found	find	VERB
ajst-25576	56	18	,	,	PUNCT
ajst-25576	56	19	the	the	DET
ajst-25576	56	20	iteration	iteration	NOUN
ajst-25576	56	21	is	be	AUX
ajst-25576	56	22	stopped	stop	VERB
ajst-25576	56	23	.	.	PUNCT
ajst-25576	57	1	output	output	VERB
ajst-25576	57	2	the	the	DET
ajst-25576	57	3	optimal	optimal	ADJ
ajst-25576	57	4	combination	combination	NOUN
ajst-25576	57	5	of	of	ADP
ajst-25576	57	6	pid	pid	NOUN
ajst-25576	57	7	parameters	parameter	NOUN
ajst-25576	57	8	.	.	PUNCT
ajst-25576	58	1	the	the	DET
ajst-25576	58	2	implementation	implementation	NOUN
ajst-25576	58	3	of	of	ADP
ajst-25576	58	4	the	the	DET
ajst-25576	58	5	algorithm	algorithm	NOUN
ajst-25576	58	6	mainly	mainly	ADV
ajst-25576	58	7	includes	include	VERB
ajst-25576	58	8	the	the	DET
ajst-25576	58	9	following	follow	VERB
ajst-25576	58	10	parts	part	NOUN
ajst-25576	58	11	:	:	PUNCT
ajst-25576	58	12	1	1	X
ajst-25576	58	13	.	.	X
ajst-25576	58	14	set	set	VERB
ajst-25576	58	15	the	the	DET
ajst-25576	58	16	initial	initial	ADJ
ajst-25576	58	17	position	position	NOUN
ajst-25576	58	18	and	and	CCONJ
ajst-25576	58	19	step	step	NOUN
ajst-25576	58	20	size	size	NOUN
ajst-25576	58	21	of	of	ADP
ajst-25576	58	22	the	the	DET
ajst-25576	58	23	longicorn	longicorn	ADJ
ajst-25576	58	24	beetle	beetle	NOUN
ajst-25576	58	25	.	.	PUNCT
ajst-25576	59	1	2	2	X
ajst-25576	59	2	.	.	X
ajst-25576	59	3	according	accord	VERB
ajst-25576	59	4	to	to	ADP
ajst-25576	59	5	the	the	DET
ajst-25576	59	6	current	current	ADJ
ajst-25576	59	7	pid	pid	NOUN
ajst-25576	59	8	parameter	parameter	NOUN
ajst-25576	59	9	combination	combination	NOUN
ajst-25576	59	10	,	,	PUNCT
ajst-25576	59	11	the	the	DET
ajst-25576	59	12	response	response	NOUN
ajst-25576	59	13	of	of	ADP
ajst-25576	59	14	the	the	DET
ajst-25576	59	15	control	control	NOUN
ajst-25576	59	16	system	system	NOUN
ajst-25576	59	17	is	be	AUX
ajst-25576	59	18	obtained	obtain	VERB
ajst-25576	59	19	through	through	ADP
ajst-25576	59	20	simulation	simulation	NOUN
ajst-25576	59	21	,	,	PUNCT
ajst-25576	59	22	and	and	CCONJ
ajst-25576	59	23	the	the	DET
ajst-25576	59	24	value	value	NOUN
ajst-25576	59	25	of	of	ADP
ajst-25576	59	26	the	the	DET
ajst-25576	59	27	objective	objective	ADJ
ajst-25576	59	28	function	function	NOUN
ajst-25576	59	29	is	be	AUX
ajst-25576	59	30	calculated	calculate	VERB
ajst-25576	59	31	.	.	PUNCT
ajst-25576	60	1	3	3	X
ajst-25576	60	2	.	.	PUNCT
ajst-25576	60	3	according	accord	VERB
ajst-25576	60	4	to	to	ADP
ajst-25576	60	5	the	the	DET
ajst-25576	60	6	principle	principle	NOUN
ajst-25576	60	7	of	of	ADP
ajst-25576	60	8	bas	bas	PROPN
ajst-25576	60	9	algorithm	algorithm	NOUN
ajst-25576	60	10	,	,	PUNCT
ajst-25576	60	11	the	the	DET
ajst-25576	60	12	position	position	NOUN
ajst-25576	60	13	(	(	PUNCT
ajst-25576	60	14	that	that	PRON
ajst-25576	60	15	is	is	ADV
ajst-25576	60	16	,	,	PUNCT
ajst-25576	60	17	pid	pid	NOUN
ajst-25576	60	18	parameters	parameter	NOUN
ajst-25576	60	19	)	)	PUNCT
ajst-25576	60	20	of	of	ADP
ajst-25576	60	21	longicorn	longicorn	ADJ
ajst-25576	60	22	beetles	beetle	NOUN
ajst-25576	60	23	is	be	AUX
ajst-25576	60	24	updated	update	VERB
ajst-25576	60	25	.	.	PUNCT
ajst-25576	61	1	4	4	X
ajst-25576	61	2	.	.	X
ajst-25576	61	3	when	when	SCONJ
ajst-25576	61	4	necessary	necessary	ADJ
ajst-25576	61	5	,	,	PUNCT
ajst-25576	61	6	random	random	ADJ
ajst-25576	61	7	disturbance	disturbance	NOUN
ajst-25576	61	8	is	be	AUX
ajst-25576	61	9	applied	apply	VERB
ajst-25576	61	10	to	to	ADP
ajst-25576	61	11	the	the	DET
ajst-25576	61	12	position	position	NOUN
ajst-25576	61	13	of	of	ADP
ajst-25576	61	14	longicorn	longicorn	ADJ
ajst-25576	61	15	beetles	beetle	NOUN
ajst-25576	61	16	.	.	PUNCT
ajst-25576	62	1	5	5	X
ajst-25576	62	2	.	.	X
ajst-25576	62	3	record	record	NOUN
ajst-25576	62	4	and	and	CCONJ
ajst-25576	62	5	update	update	VERB
ajst-25576	62	6	the	the	DET
ajst-25576	62	7	historical	historical	ADJ
ajst-25576	62	8	optimal	optimal	ADJ
ajst-25576	62	9	solution	solution	NOUN
ajst-25576	62	10	.	.	PUNCT
ajst-25576	63	1	the	the	DET
ajst-25576	63	2	algorithm	algorithm	NOUN
ajst-25576	63	3	flow	flow	NOUN
ajst-25576	63	4	chart	chart	NOUN
ajst-25576	63	5	is	be	AUX
ajst-25576	63	6	shown	show	VERB
ajst-25576	63	7	in	in	ADP
ajst-25576	63	8	figure	figure	NOUN
ajst-25576	63	9	1	1	NUM
ajst-25576	63	10	below	below	ADV
ajst-25576	63	11	:	:	PUNCT
ajst-25576	63	12	figure	figure	NOUN
ajst-25576	63	13	1	1	NUM
ajst-25576	63	14	.	.	PUNCT
ajst-25576	64	1	algorithm	algorithm	NOUN
ajst-25576	64	2	flow	flow	VERB
ajst-25576	64	3	74	74	NUM
ajst-25576	64	4	4	4	NUM
ajst-25576	64	5	.	.	PUNCT
ajst-25576	64	6	simulation	simulation	NOUN
ajst-25576	64	7	experiment	experiment	NOUN
ajst-25576	64	8	and	and	CCONJ
ajst-25576	64	9	result	result	VERB
ajst-25576	64	10	analysis	analysis	NOUN
ajst-25576	64	11	the	the	DET
ajst-25576	64	12	experimental	experimental	ADJ
ajst-25576	64	13	environment	environment	NOUN
ajst-25576	64	14	adopts	adopt	VERB
ajst-25576	64	15	matlab	matlab	PROPN
ajst-25576	64	16	/	/	SYM
ajst-25576	64	17	simulink	simulink	PROPN
ajst-25576	64	18	,	,	PUNCT
ajst-25576	64	19	which	which	PRON
ajst-25576	64	20	is	be	AUX
ajst-25576	64	21	a	a	DET
ajst-25576	64	22	platform	platform	NOUN
ajst-25576	64	23	widely	widely	ADV
ajst-25576	64	24	used	use	VERB
ajst-25576	64	25	for	for	ADP
ajst-25576	64	26	control	control	NOUN
ajst-25576	64	27	system	system	NOUN
ajst-25576	64	28	design	design	NOUN
ajst-25576	64	29	and	and	CCONJ
ajst-25576	64	30	simulation	simulation	NOUN
ajst-25576	64	31	.	.	PUNCT
ajst-25576	65	1	the	the	DET
ajst-25576	65	2	controlled	control	VERB
ajst-25576	65	3	object	object	NOUN
ajst-25576	65	4	is	be	AUX
ajst-25576	65	5	selected	select	VERB
ajst-25576	65	6	as	as	ADP
ajst-25576	65	7	a	a	DET
ajst-25576	65	8	typical	typical	ADJ
ajst-25576	65	9	second	second	ADJ
ajst-25576	65	10	-	-	PUNCT
ajst-25576	65	11	order	order	NOUN
ajst-25576	65	12	system	system	NOUN
ajst-25576	65	13	,	,	PUNCT
ajst-25576	65	14	and	and	CCONJ
ajst-25576	65	15	its	its	PRON
ajst-25576	65	16	transfer	transfer	NOUN
ajst-25576	65	17	function	function	NOUN
ajst-25576	65	18	is	be	AUX
ajst-25576	65	19	as	as	SCONJ
ajst-25576	65	20	follows	follow	VERB
ajst-25576	65	21	:	:	PUNCT
ajst-25576	66	1			NOUN
ajst-25576	66	2			PROPN
ajst-25576	66	3	22	22	NUM
ajst-25576	66	4	2	2	NUM
ajst-25576	66	5	2	2	NUM
ajst-25576	66	6	nn	nn	NOUN
ajst-25576	66	7	n	n	SYM
ajst-25576	66	8	ss	ss	NOUN
ajst-25576	66	9	sg	sg	INTJ
ajst-25576	66	10			PUNCT
ajst-25576	66	11			PROPN
ajst-25576	66	12			PROPN
ajst-25576	66	13			PROPN
ajst-25576	66	14	(	(	PUNCT
ajst-25576	66	15	4	4	NUM
ajst-25576	66	16	)	)	PUNCT
ajst-25576	66	17	where	where	SCONJ
ajst-25576	66	18	n	n	PROPN
ajst-25576	66	19	is	be	AUX
ajst-25576	66	20	the	the	DET
ajst-25576	66	21	natural	natural	ADJ
ajst-25576	66	22	frequency	frequency	NOUN
ajst-25576	66	23	and	and	CCONJ
ajst-25576	66	24			NOUN
ajst-25576	66	25	is	be	AUX
ajst-25576	66	26	the	the	DET
ajst-25576	66	27	damping	damp	VERB
ajst-25576	66	28	ratio	ratio	NOUN
ajst-25576	66	29	.	.	PUNCT
ajst-25576	67	1	in	in	ADP
ajst-25576	67	2	order	order	NOUN
ajst-25576	67	3	to	to	PART
ajst-25576	67	4	simulate	simulate	VERB
ajst-25576	67	5	different	different	ADJ
ajst-25576	67	6	system	system	NOUN
ajst-25576	67	7	dynamics	dynamic	NOUN
ajst-25576	67	8	,	,	PUNCT
ajst-25576	67	9	these	these	DET
ajst-25576	67	10	parameters	parameter	NOUN
ajst-25576	67	11	are	be	AUX
ajst-25576	67	12	changed	change	VERB
ajst-25576	67	13	in	in	ADP
ajst-25576	67	14	the	the	DET
ajst-25576	67	15	experiment	experiment	NOUN
ajst-25576	67	16	.	.	PUNCT
ajst-25576	68	1	specific	specific	ADJ
ajst-25576	68	2	parameter	parameter	NOUN
ajst-25576	68	3	settings	setting	NOUN
ajst-25576	68	4	are	be	AUX
ajst-25576	68	5	as	as	SCONJ
ajst-25576	68	6	follows	follow	VERB
ajst-25576	68	7	:	:	PUNCT
ajst-25576	68	8	initial	initial	ADJ
ajst-25576	68	9	pid	pid	NOUN
ajst-25576	68	10	parameters	parameter	NOUN
ajst-25576	68	11	range	range	VERB
ajst-25576	68	12	:	:	PUNCT
ajst-25576	68	13	pk	pk	NOUN
ajst-25576	68	14	:	:	PUNCT
ajst-25576	68	15	0.1	0.1	NUM
ajst-25576	68	16	to	to	PART
ajst-25576	68	17	10	10	NUM
ajst-25576	68	18	,	,	PUNCT
ajst-25576	68	19	ik	ik	PROPN
ajst-25576	68	20	:	:	PUNCT
ajst-25576	68	21	0.01	0.01	NUM
ajst-25576	68	22	to	to	PART
ajst-25576	68	23	1	1	NUM
ajst-25576	68	24	,	,	PUNCT
ajst-25576	68	25	dk	dk	X
ajst-25576	68	26	:	:	PUNCT
ajst-25576	68	27	0.01	0.01	NUM
ajst-25576	68	28	to	to	PART
ajst-25576	68	29	1	1	NUM
ajst-25576	68	30	.	.	PUNCT
ajst-25576	68	31	step	step	NOUN
ajst-25576	68	32	adjustment	adjustment	NOUN
ajst-25576	68	33	strategy	strategy	NOUN
ajst-25576	68	34	:	:	PUNCT
ajst-25576	68	35	initial	initial	ADJ
ajst-25576	68	36	step	step	NOUN
ajst-25576	68	37	10	10	NUM
ajst-25576	68	38	s	s	ADV
ajst-25576	68	39	,	,	PUNCT
ajst-25576	68	40	step	step	NOUN
ajst-25576	68	41	attenuation	attenuation	NOUN
ajst-25576	68	42	factor	factor	NOUN
ajst-25576	68	43	95.0	95.0	NUM
ajst-25576	68	44	random	random	ADJ
ajst-25576	68	45	disturbance	disturbance	NOUN
ajst-25576	68	46	mechanism	mechanism	NOUN
ajst-25576	68	47	:	:	PUNCT
ajst-25576	68	48	disturbance	disturbance	NOUN
ajst-25576	68	49	coefficient	coefficient	NOUN
ajst-25576	68	50	1.0	1.0	NUM
ajst-25576	68	51	,	,	PUNCT
ajst-25576	68	52	random	random	ADJ
ajst-25576	68	53	number	number	NOUN
ajst-25576	68	54	range	range	NOUN
ajst-25576	68	55	-1	-1	ADP
ajst-25576	68	56	to	to	ADP
ajst-25576	68	57	1	1	NUM
ajst-25576	68	58	.	.	PUNCT
ajst-25576	69	1	elite	elite	ADJ
ajst-25576	69	2	retention	retention	NOUN
ajst-25576	69	3	strategy	strategy	NOUN
ajst-25576	69	4	:	:	PUNCT
ajst-25576	69	5	record	record	NOUN
ajst-25576	69	6	and	and	CCONJ
ajst-25576	69	7	retain	retain	VERB
ajst-25576	69	8	the	the	DET
ajst-25576	69	9	variables	variable	NOUN
ajst-25576	69	10	of	of	ADP
ajst-25576	69	11	historical	historical	ADJ
ajst-25576	69	12	optimal	optimal	ADJ
ajst-25576	69	13	solution	solution	NOUN
ajst-25576	69	14	.	.	PUNCT
ajst-25576	70	1	in	in	ADP
ajst-25576	70	2	order	order	NOUN
ajst-25576	70	3	to	to	PART
ajst-25576	70	4	ensure	ensure	VERB
ajst-25576	70	5	the	the	DET
ajst-25576	70	6	reliability	reliability	NOUN
ajst-25576	70	7	of	of	ADP
ajst-25576	70	8	the	the	DET
ajst-25576	70	9	results	result	NOUN
ajst-25576	70	10	,	,	PUNCT
ajst-25576	70	11	experiments	experiment	NOUN
ajst-25576	70	12	are	be	AUX
ajst-25576	70	13	repeated	repeat	VERB
ajst-25576	70	14	for	for	ADP
ajst-25576	70	15	each	each	DET
ajst-25576	70	16	controlled	control	VERB
ajst-25576	70	17	object	object	NOUN
ajst-25576	70	18	model	model	NOUN
ajst-25576	70	19	,	,	PUNCT
ajst-25576	70	20	and	and	CCONJ
ajst-25576	70	21	the	the	DET
ajst-25576	70	22	average	average	ADJ
ajst-25576	70	23	value	value	NOUN
ajst-25576	70	24	is	be	AUX
ajst-25576	70	25	taken	take	VERB
ajst-25576	70	26	as	as	ADP
ajst-25576	70	27	the	the	DET
ajst-25576	70	28	final	final	ADJ
ajst-25576	70	29	result	result	NOUN
ajst-25576	70	30	.	.	PUNCT
ajst-25576	71	1	the	the	DET
ajst-25576	71	2	improved	improved	ADJ
ajst-25576	71	3	bas	bas	PROPN
ajst-25576	71	4	algorithm	algorithm	NOUN
ajst-25576	71	5	significantly	significantly	ADV
ajst-25576	71	6	improves	improve	VERB
ajst-25576	71	7	the	the	DET
ajst-25576	71	8	convergence	convergence	NOUN
ajst-25576	71	9	speed	speed	NOUN
ajst-25576	71	10	by	by	ADP
ajst-25576	71	11	dynamically	dynamically	ADV
ajst-25576	71	12	adjusting	adjust	VERB
ajst-25576	71	13	the	the	DET
ajst-25576	71	14	step	step	NOUN
ajst-25576	71	15	size	size	NOUN
ajst-25576	71	16	,	,	PUNCT
ajst-25576	71	17	introducing	introduce	VERB
ajst-25576	71	18	random	random	ADJ
ajst-25576	71	19	disturbance	disturbance	NOUN
ajst-25576	71	20	and	and	CCONJ
ajst-25576	71	21	elite	elite	ADJ
ajst-25576	71	22	retention	retention	NOUN
ajst-25576	71	23	strategy	strategy	NOUN
ajst-25576	71	24	.	.	PUNCT
ajst-25576	72	1	compared	compare	VERB
ajst-25576	72	2	with	with	ADP
ajst-25576	72	3	the	the	DET
ajst-25576	72	4	traditional	traditional	ADJ
ajst-25576	72	5	method	method	NOUN
ajst-25576	72	6	,	,	PUNCT
ajst-25576	72	7	the	the	DET
ajst-25576	72	8	algorithm	algorithm	NOUN
ajst-25576	72	9	can	can	AUX
ajst-25576	72	10	find	find	VERB
ajst-25576	72	11	the	the	DET
ajst-25576	72	12	near	near	ADV
ajst-25576	72	13	-	-	PUNCT
ajst-25576	72	14	optimal	optimal	ADJ
ajst-25576	72	15	pid	pid	NOUN
ajst-25576	72	16	parameters	parameter	NOUN
ajst-25576	72	17	in	in	ADP
ajst-25576	72	18	less	less	ADJ
ajst-25576	72	19	iterations	iteration	NOUN
ajst-25576	72	20	(	(	PUNCT
ajst-25576	72	21	figure	figure	NOUN
ajst-25576	72	22	2	2	NUM
ajst-25576	72	23	)	)	PUNCT
ajst-25576	72	24	.	.	PUNCT
ajst-25576	73	1	the	the	DET
ajst-25576	73	2	objective	objective	ADJ
ajst-25576	73	3	function	function	NOUN
ajst-25576	73	4	value	value	NOUN
ajst-25576	73	5	of	of	ADP
ajst-25576	73	6	the	the	DET
ajst-25576	73	7	improved	improve	VERB
ajst-25576	73	8	bas	bas	PROPN
ajst-25576	73	9	algorithm	algorithm	NOUN
ajst-25576	73	10	decreases	decrease	VERB
ajst-25576	73	11	rapidly	rapidly	ADV
ajst-25576	73	12	with	with	ADP
ajst-25576	73	13	the	the	DET
ajst-25576	73	14	increase	increase	NOUN
ajst-25576	73	15	of	of	ADP
ajst-25576	73	16	iteration	iteration	NOUN
ajst-25576	73	17	times	time	NOUN
ajst-25576	73	18	,	,	PUNCT
ajst-25576	73	19	showing	show	VERB
ajst-25576	73	20	a	a	DET
ajst-25576	73	21	faster	fast	ADV
ajst-25576	73	22	initial	initial	ADJ
ajst-25576	73	23	convergence	convergence	NOUN
ajst-25576	73	24	speed	speed	NOUN
ajst-25576	73	25	.	.	PUNCT
ajst-25576	74	1	the	the	DET
ajst-25576	74	2	improved	improved	ADJ
ajst-25576	74	3	bas	bas	PROPN
ajst-25576	74	4	algorithm	algorithm	NOUN
ajst-25576	74	5	keeps	keep	VERB
ajst-25576	74	6	a	a	DET
ajst-25576	74	7	lower	low	ADJ
ajst-25576	74	8	objective	objective	ADJ
ajst-25576	74	9	function	function	NOUN
ajst-25576	74	10	value	value	NOUN
ajst-25576	74	11	in	in	ADP
ajst-25576	74	12	the	the	DET
ajst-25576	74	13	later	later	ADJ
ajst-25576	74	14	iteration	iteration	NOUN
ajst-25576	74	15	,	,	PUNCT
ajst-25576	74	16	which	which	PRON
ajst-25576	74	17	shows	show	VERB
ajst-25576	74	18	that	that	SCONJ
ajst-25576	74	19	its	its	PRON
ajst-25576	74	20	optimization	optimization	NOUN
ajst-25576	74	21	effect	effect	NOUN
ajst-25576	74	22	is	be	AUX
ajst-25576	74	23	better	well	ADJ
ajst-25576	74	24	.	.	PUNCT
ajst-25576	75	1	there	there	PRON
ajst-25576	75	2	are	be	VERB
ajst-25576	75	3	fluctuations	fluctuation	NOUN
ajst-25576	75	4	in	in	ADP
ajst-25576	75	5	the	the	DET
ajst-25576	75	6	objective	objective	ADJ
ajst-25576	75	7	function	function	NOUN
ajst-25576	75	8	curves	curve	NOUN
ajst-25576	75	9	of	of	ADP
ajst-25576	75	10	the	the	DET
ajst-25576	75	11	two	two	NUM
ajst-25576	75	12	methods	method	NOUN
ajst-25576	75	13	,	,	PUNCT
ajst-25576	75	14	but	but	CCONJ
ajst-25576	75	15	the	the	DET
ajst-25576	75	16	fluctuation	fluctuation	NOUN
ajst-25576	75	17	amplitude	amplitude	NOUN
ajst-25576	75	18	of	of	ADP
ajst-25576	75	19	the	the	DET
ajst-25576	75	20	improved	improved	ADJ
ajst-25576	75	21	bas	bas	PROPN
ajst-25576	75	22	algorithm	algorithm	NOUN
ajst-25576	75	23	is	be	AUX
ajst-25576	75	24	relatively	relatively	ADV
ajst-25576	75	25	small	small	ADJ
ajst-25576	75	26	,	,	PUNCT
ajst-25576	75	27	showing	show	VERB
ajst-25576	75	28	better	well	ADJ
ajst-25576	75	29	stability	stability	NOUN
ajst-25576	75	30	.	.	PUNCT
ajst-25576	76	1	compared	compare	VERB
ajst-25576	76	2	with	with	ADP
ajst-25576	76	3	the	the	DET
ajst-25576	76	4	traditional	traditional	ADJ
ajst-25576	76	5	method	method	NOUN
ajst-25576	76	6	,	,	PUNCT
ajst-25576	76	7	the	the	DET
ajst-25576	76	8	improved	improved	ADJ
ajst-25576	76	9	bas	bas	PROPN
ajst-25576	76	10	algorithm	algorithm	NOUN
ajst-25576	76	11	not	not	PART
ajst-25576	76	12	only	only	ADV
ajst-25576	76	13	has	have	VERB
ajst-25576	76	14	fast	fast	ADJ
ajst-25576	76	15	initial	initial	ADJ
ajst-25576	76	16	convergence	convergence	NOUN
ajst-25576	76	17	speed	speed	NOUN
ajst-25576	76	18	,	,	PUNCT
ajst-25576	76	19	but	but	CCONJ
ajst-25576	76	20	also	also	ADV
ajst-25576	76	21	can	can	AUX
ajst-25576	76	22	stabilize	stabilize	VERB
ajst-25576	76	23	near	near	ADP
ajst-25576	76	24	the	the	DET
ajst-25576	76	25	optimal	optimal	ADJ
ajst-25576	76	26	solution	solution	NOUN
ajst-25576	76	27	with	with	ADP
ajst-25576	76	28	a	a	DET
ajst-25576	76	29	lower	low	ADJ
ajst-25576	76	30	objective	objective	ADJ
ajst-25576	76	31	function	function	NOUN
ajst-25576	76	32	value	value	NOUN
ajst-25576	76	33	,	,	PUNCT
ajst-25576	76	34	showing	show	VERB
ajst-25576	76	35	better	well	ADJ
ajst-25576	76	36	optimization	optimization	NOUN
ajst-25576	76	37	performance	performance	NOUN
ajst-25576	76	38	.	.	PUNCT
ajst-25576	77	1	the	the	DET
ajst-25576	77	2	curve	curve	NOUN
ajst-25576	77	3	fluctuation	fluctuation	NOUN
ajst-25576	77	4	of	of	ADP
ajst-25576	77	5	the	the	DET
ajst-25576	77	6	improved	improved	ADJ
ajst-25576	77	7	bas	bas	PROPN
ajst-25576	77	8	algorithm	algorithm	NOUN
ajst-25576	77	9	is	be	AUX
ajst-25576	77	10	smaller	small	ADJ
ajst-25576	77	11	,	,	PUNCT
ajst-25576	77	12	which	which	PRON
ajst-25576	77	13	means	mean	VERB
ajst-25576	77	14	that	that	SCONJ
ajst-25576	77	15	it	it	PRON
ajst-25576	77	16	has	have	VERB
ajst-25576	77	17	stronger	strong	ADJ
ajst-25576	77	18	resistance	resistance	NOUN
ajst-25576	77	19	to	to	ADP
ajst-25576	77	20	disturbance	disturbance	NOUN
ajst-25576	77	21	and	and	CCONJ
ajst-25576	77	22	better	well	ADJ
ajst-25576	77	23	stability	stability	NOUN
ajst-25576	77	24	in	in	ADP
ajst-25576	77	25	the	the	DET
ajst-25576	77	26	iterative	iterative	NOUN
ajst-25576	77	27	process	process	NOUN
ajst-25576	77	28	.	.	PUNCT
ajst-25576	78	1	in	in	ADP
ajst-25576	78	2	the	the	DET
ajst-25576	78	3	optimization	optimization	NOUN
ajst-25576	78	4	of	of	ADP
ajst-25576	78	5	pid	pid	NOUN
ajst-25576	78	6	parameters	parameter	NOUN
ajst-25576	78	7	,	,	PUNCT
ajst-25576	78	8	the	the	DET
ajst-25576	78	9	improved	improve	VERB
ajst-25576	78	10	longicorn	longicorn	ADJ
ajst-25576	78	11	search	search	NOUN
ajst-25576	78	12	algorithm	algorithm	NOUN
ajst-25576	78	13	has	have	VERB
ajst-25576	78	14	obvious	obvious	ADJ
ajst-25576	78	15	advantages	advantage	NOUN
ajst-25576	78	16	over	over	ADP
ajst-25576	78	17	the	the	DET
ajst-25576	78	18	traditional	traditional	ADJ
ajst-25576	78	19	methods	method	NOUN
ajst-25576	78	20	,	,	PUNCT
ajst-25576	78	21	and	and	CCONJ
ajst-25576	78	22	shows	show	VERB
ajst-25576	78	23	better	well	ADJ
ajst-25576	78	24	performance	performance	NOUN
ajst-25576	78	25	in	in	ADP
ajst-25576	78	26	convergence	convergence	NOUN
ajst-25576	78	27	speed	speed	NOUN
ajst-25576	78	28	and	and	CCONJ
ajst-25576	78	29	stability	stability	NOUN
ajst-25576	78	30	.	.	PUNCT
ajst-25576	79	1	this	this	PRON
ajst-25576	79	2	provides	provide	VERB
ajst-25576	79	3	a	a	DET
ajst-25576	79	4	more	more	ADV
ajst-25576	79	5	efficient	efficient	ADJ
ajst-25576	79	6	and	and	CCONJ
ajst-25576	79	7	stable	stable	ADJ
ajst-25576	79	8	parameter	parameter	NOUN
ajst-25576	79	9	optimization	optimization	NOUN
ajst-25576	79	10	approach	approach	NOUN
ajst-25576	79	11	for	for	ADP
ajst-25576	79	12	control	control	NOUN
ajst-25576	79	13	system	system	NOUN
ajst-25576	79	14	design	design	NOUN
ajst-25576	79	15	.	.	PUNCT
ajst-25576	80	1	figure	figure	NOUN
ajst-25576	80	2	2	2	NUM
ajst-25576	80	3	.	.	PUNCT
ajst-25576	81	1	comparison	comparison	NOUN
ajst-25576	81	2	of	of	ADP
ajst-25576	81	3	convergence	convergence	NOUN
ajst-25576	81	4	speed	speed	NOUN
ajst-25576	81	5	by	by	ADP
ajst-25576	81	6	comparing	compare	VERB
ajst-25576	81	7	the	the	DET
ajst-25576	81	8	performance	performance	NOUN
ajst-25576	81	9	of	of	ADP
ajst-25576	81	10	pid	pid	NOUN
ajst-25576	81	11	controller	controller	NOUN
ajst-25576	81	12	tuned	tune	VERB
ajst-25576	81	13	by	by	ADP
ajst-25576	81	14	traditional	traditional	ADJ
ajst-25576	81	15	method	method	NOUN
ajst-25576	81	16	and	and	CCONJ
ajst-25576	81	17	improved	improve	VERB
ajst-25576	81	18	bas	bas	PROPN
ajst-25576	81	19	algorithm	algorithm	NOUN
ajst-25576	81	20	,	,	PUNCT
ajst-25576	81	21	it	it	PRON
ajst-25576	81	22	is	be	AUX
ajst-25576	81	23	found	find	VERB
ajst-25576	81	24	that	that	SCONJ
ajst-25576	81	25	the	the	DET
ajst-25576	81	26	latter	latter	NOUN
ajst-25576	81	27	has	have	VERB
ajst-25576	81	28	better	well	ADJ
ajst-25576	81	29	performance	performance	NOUN
ajst-25576	81	30	in	in	ADP
ajst-25576	81	31	overshoot	overshoot	NOUN
ajst-25576	81	32	,	,	PUNCT
ajst-25576	81	33	adjustment	adjustment	NOUN
ajst-25576	81	34	time	time	NOUN
ajst-25576	81	35	and	and	CCONJ
ajst-25576	81	36	steady	steady	ADJ
ajst-25576	81	37	-	-	PUNCT
ajst-25576	81	38	state	state	NOUN
ajst-25576	81	39	error	error	NOUN
ajst-25576	81	40	(	(	PUNCT
ajst-25576	81	41	table	table	NOUN
ajst-25576	81	42	1	1	NUM
ajst-25576	81	43	)	)	PUNCT
ajst-25576	81	44	.	.	PUNCT
ajst-25576	82	1	table	table	NOUN
ajst-25576	82	2	1	1	NUM
ajst-25576	82	3	.	.	PUNCT
ajst-25576	83	1	performance	performance	NOUN
ajst-25576	83	2	comparison	comparison	NOUN
ajst-25576	83	3	iterations	iteration	NOUN
ajst-25576	83	4	method	method	VERB
ajst-25576	83	5	objective	objective	ADJ
ajst-25576	83	6	function	function	NOUN
ajst-25576	83	7	value	value	NOUN
ajst-25576	83	8	overshoot	overshoot	NOUN
ajst-25576	83	9	(	(	PUNCT
ajst-25576	83	10	%	%	INTJ
ajst-25576	83	11	)	)	PUNCT
ajst-25576	83	12	adjustment	adjustment	NOUN
ajst-25576	83	13	time	time	NOUN
ajst-25576	83	14	(	(	PUNCT
ajst-25576	83	15	s	s	NOUN
ajst-25576	83	16	)	)	PUNCT
ajst-25576	83	17	steady	steady	ADJ
ajst-25576	83	18	state	state	NOUN
ajst-25576	83	19	error	error	NOUN
ajst-25576	83	20	(	(	PUNCT
ajst-25576	83	21	%	%	NOUN
ajst-25576	83	22	)	)	PUNCT
ajst-25576	83	23	10	10	NUM
ajst-25576	83	24	traditional	traditional	ADJ
ajst-25576	83	25	method	method	NOUN
ajst-25576	83	26	0.85	0.85	NUM
ajst-25576	83	27	25.0	25.0	NUM
ajst-25576	83	28	6.0	6.0	NUM
ajst-25576	83	29	3.0	3.0	NUM
ajst-25576	83	30	improved	improve	VERB
ajst-25576	83	31	bas	bas	PROPN
ajst-25576	83	32	algorithm	algorithm	NOUN
ajst-25576	83	33	0.70	0.70	NUM
ajst-25576	83	34	20.0	20.0	NUM
ajst-25576	83	35	5.0	5.0	NUM
ajst-25576	83	36	2.0	2.0	NUM
ajst-25576	83	37	20	20	NUM
ajst-25576	83	38	traditional	traditional	ADJ
ajst-25576	83	39	method	method	NOUN
ajst-25576	83	40	0.80	0.80	NUM
ajst-25576	83	41	23.0	23.0	NUM
ajst-25576	83	42	5.5	5.5	NUM
ajst-25576	83	43	2.8	2.8	NUM
ajst-25576	83	44	improved	improve	VERB
ajst-25576	83	45	bas	bas	PROPN
ajst-25576	83	46	algorithm	algorithm	NOUN
ajst-25576	83	47	0.65	0.65	NUM
ajst-25576	83	48	18.0	18.0	NUM
ajst-25576	83	49	4.5	4.5	NUM
ajst-25576	83	50	1.5	1.5	NUM
ajst-25576	83	51	30	30	NUM
ajst-25576	83	52	traditional	traditional	ADJ
ajst-25576	83	53	method	method	NOUN
ajst-25576	83	54	0.77	0.77	NUM
ajst-25576	83	55	22.0	22.0	NUM
ajst-25576	83	56	5.2	5.2	NUM
ajst-25576	83	57	2.6	2.6	NUM
ajst-25576	83	58	improved	improve	VERB
ajst-25576	83	59	bas	bas	PROPN
ajst-25576	83	60	algorithm	algorithm	NOUN
ajst-25576	83	61	0.62	0.62	NUM
ajst-25576	83	62	16.0	16.0	NUM
ajst-25576	83	63	4.2	4.2	NUM
ajst-25576	83	64	1.2	1.2	NUM
ajst-25576	83	65	100	100	NUM
ajst-25576	83	66	traditional	traditional	ADJ
ajst-25576	83	67	method	method	NOUN
ajst-25576	83	68	0.72	0.72	NUM
ajst-25576	83	69	20.0	20.0	NUM
ajst-25576	83	70	4.8	4.8	NUM
ajst-25576	83	71	2.2	2.2	NUM
ajst-25576	83	72	improved	improve	VERB
ajst-25576	83	73	bas	bas	PROPN
ajst-25576	83	74	algorithm	algorithm	NOUN
ajst-25576	83	75	0.58	0.58	NUM
ajst-25576	83	76	14.0	14.0	NUM
ajst-25576	83	77	3.8	3.8	NUM
ajst-25576	83	78	0.8	0.8	NUM
ajst-25576	83	79	judging	judge	VERB
ajst-25576	83	80	from	from	ADP
ajst-25576	83	81	the	the	DET
ajst-25576	83	82	objective	objective	ADJ
ajst-25576	83	83	function	function	NOUN
ajst-25576	83	84	value	value	NOUN
ajst-25576	83	85	,	,	PUNCT
ajst-25576	83	86	the	the	DET
ajst-25576	83	87	improved	improved	ADJ
ajst-25576	83	88	bas	bas	PROPN
ajst-25576	83	89	algorithm	algorithm	NOUN
ajst-25576	83	90	has	have	AUX
ajst-25576	83	91	achieved	achieve	VERB
ajst-25576	83	92	a	a	DET
ajst-25576	83	93	lower	low	ADJ
ajst-25576	83	94	objective	objective	ADJ
ajst-25576	83	95	function	function	NOUN
ajst-25576	83	96	value	value	NOUN
ajst-25576	83	97	than	than	ADP
ajst-25576	83	98	the	the	DET
ajst-25576	83	99	traditional	traditional	ADJ
ajst-25576	83	100	method	method	NOUN
ajst-25576	83	101	in	in	ADP
ajst-25576	83	102	each	each	DET
ajst-25576	83	103	iteration	iteration	NOUN
ajst-25576	83	104	.	.	PUNCT
ajst-25576	84	1	the	the	DET
ajst-25576	84	2	improved	improved	ADJ
ajst-25576	84	3	bas	bas	PROPN
ajst-25576	84	4	algorithm	algorithm	NOUN
ajst-25576	84	5	demonstrates	demonstrate	VERB
ajst-25576	84	6	a	a	DET
ajst-25576	84	7	superior	superior	ADJ
ajst-25576	84	8	capacity	capacity	NOUN
ajst-25576	84	9	to	to	ADP
ajst-25576	84	10	fine	fine	ADJ
ajst-25576	84	11	-	-	PUNCT
ajst-25576	84	12	tune	tune	NOUN
ajst-25576	84	13	these	these	DET
ajst-25576	84	14	metrics	metric	NOUN
ajst-25576	84	15	upon	upon	SCONJ
ajst-25576	84	16	taking	take	VERB
ajst-25576	84	17	into	into	ADP
ajst-25576	84	18	account	account	NOUN
ajst-25576	84	19	pivotal	pivotal	ADJ
ajst-25576	84	20	performance	performance	NOUN
ajst-25576	84	21	indicators	indicator	NOUN
ajst-25576	84	22	such	such	ADJ
ajst-25576	84	23	as	as	ADP
ajst-25576	84	24	overshoot	overshoot	NOUN
ajst-25576	84	25	,	,	PUNCT
ajst-25576	84	26	adjustment	adjustment	NOUN
ajst-25576	84	27	time	time	NOUN
ajst-25576	84	28	,	,	PUNCT
ajst-25576	84	29	and	and	CCONJ
ajst-25576	84	30	steadystate	steadystate	VERB
ajst-25576	84	31	error	error	NOUN
ajst-25576	84	32	,	,	PUNCT
ajst-25576	84	33	thereby	thereby	ADV
ajst-25576	84	34	ensuring	ensure	VERB
ajst-25576	84	35	an	an	DET
ajst-25576	84	36	elevated	elevated	ADJ
ajst-25576	84	37	overall	overall	ADJ
ajst-25576	84	38	system	system	NOUN
ajst-25576	84	39	performance	performance	NOUN
ajst-25576	84	40	.	.	PUNCT
ajst-25576	85	1	in	in	ADP
ajst-25576	85	2	the	the	DET
ajst-25576	85	3	domain	domain	NOUN
ajst-25576	85	4	of	of	ADP
ajst-25576	85	5	overshoot	overshoot	NOUN
ajst-25576	85	6	,	,	PUNCT
ajst-25576	85	7	the	the	DET
ajst-25576	85	8	improved	improved	ADJ
ajst-25576	85	9	bas	bas	PROPN
ajst-25576	85	10	algorithm	algorithm	NOUN
ajst-25576	85	11	manifests	manifest	VERB
ajst-25576	85	12	a	a	DET
ajst-25576	85	13	markedly	markedly	ADV
ajst-25576	85	14	lower	low	ADJ
ajst-25576	85	15	overshoot	overshoot	NOUN
ajst-25576	85	16	compared	compare	VERB
ajst-25576	85	17	to	to	ADP
ajst-25576	85	18	conventional	conventional	ADJ
ajst-25576	85	19	methods	method	NOUN
ajst-25576	85	20	.	.	PUNCT
ajst-25576	86	1	overshoot	overshoot	NOUN
ajst-25576	86	2	represents	represent	VERB
ajst-25576	86	3	the	the	DET
ajst-25576	86	4	maximum	maximum	ADJ
ajst-25576	86	5	variance	variance	NOUN
ajst-25576	86	6	beyond	beyond	ADP
ajst-25576	86	7	the	the	DET
ajst-25576	86	8	steady	steady	ADJ
ajst-25576	86	9	-	-	PUNCT
ajst-25576	86	10	state	state	NOUN
ajst-25576	86	11	value	value	NOUN
ajst-25576	86	12	during	during	ADP
ajst-25576	86	13	system	system	NOUN
ajst-25576	86	14	transition	transition	NOUN
ajst-25576	86	15	.	.	PUNCT
ajst-25576	87	1	a	a	DET
ajst-25576	87	2	diminished	diminished	ADJ
ajst-25576	87	3	overshoot	overshoot	NOUN
ajst-25576	87	4	signifies	signify	VERB
ajst-25576	87	5	a	a	DET
ajst-25576	87	6	smoother	smooth	ADJ
ajst-25576	87	7	attainment	attainment	NOUN
ajst-25576	87	8	of	of	ADP
ajst-25576	87	9	steady	steady	ADJ
ajst-25576	87	10	state	state	NOUN
ajst-25576	87	11	,	,	PUNCT
ajst-25576	87	12	consequently	consequently	ADV
ajst-25576	87	13	mitigating	mitigate	VERB
ajst-25576	87	14	system	system	NOUN
ajst-25576	87	15	impact	impact	NOUN
ajst-25576	87	16	and	and	CCONJ
ajst-25576	87	17	oscillation	oscillation	NOUN
ajst-25576	87	18	.	.	PUNCT
ajst-25576	88	1	the	the	DET
ajst-25576	88	2	adjustment	adjustment	NOUN
ajst-25576	88	3	period	period	NOUN
ajst-25576	88	4	associated	associate	VERB
ajst-25576	88	5	with	with	ADP
ajst-25576	88	6	the	the	DET
ajst-25576	88	7	improved	improved	ADJ
ajst-25576	88	8	bas	bas	PROPN
ajst-25576	88	9	algorithm	algorithm	NOUN
ajst-25576	88	10	is	be	AUX
ajst-25576	88	11	typically	typically	ADV
ajst-25576	88	12	curtailed	curtail	VERB
ajst-25576	88	13	in	in	ADP
ajst-25576	88	14	comparison	comparison	NOUN
ajst-25576	88	15	with	with	ADP
ajst-25576	88	16	traditional	traditional	ADJ
ajst-25576	88	17	techniques	technique	NOUN
ajst-25576	88	18	.	.	PUNCT
ajst-25576	89	1	this	this	DET
ajst-25576	89	2	adjustment	adjustment	NOUN
ajst-25576	89	3	time	time	NOUN
ajst-25576	89	4	denotes	denote	VERB
ajst-25576	89	5	the	the	DET
ajst-25576	89	6	duration	duration	NOUN
ajst-25576	89	7	necessary	necessary	ADJ
ajst-25576	89	8	for	for	ADP
ajst-25576	89	9	the	the	DET
ajst-25576	89	10	system	system	NOUN
ajst-25576	89	11	's	's	PART
ajst-25576	89	12	transition	transition	NOUN
ajst-25576	89	13	from	from	ADP
ajst-25576	89	14	its	its	PRON
ajst-25576	89	15	initial	initial	NOUN
ajst-25576	89	16	to	to	ADP
ajst-25576	89	17	its	its	PRON
ajst-25576	89	18	steady	steady	ADJ
ajst-25576	89	19	-	-	PUNCT
ajst-25576	89	20	state	state	NOUN
ajst-25576	89	21	configuration	configuration	NOUN
ajst-25576	89	22	.	.	PUNCT
ajst-25576	90	1	a	a	DET
ajst-25576	90	2	truncated	truncate	VERB
ajst-25576	90	3	adjustment	adjustment	NOUN
ajst-25576	90	4	duration	duration	NOUN
ajst-25576	90	5	indicates	indicate	VERB
ajst-25576	90	6	a	a	DET
ajst-25576	90	7	swifter	swifter	ADJ
ajst-25576	90	8	achievement	achievement	NOUN
ajst-25576	90	9	of	of	ADP
ajst-25576	90	10	steady	steady	ADJ
ajst-25576	90	11	state	state	NOUN
ajst-25576	90	12	,	,	PUNCT
ajst-25576	90	13	thus	thus	ADV
ajst-25576	90	14	augmenting	augment	VERB
ajst-25576	90	15	the	the	DET
ajst-25576	90	16	system	system	NOUN
ajst-25576	90	17	's	's	PART
ajst-25576	90	18	response	response	NOUN
ajst-25576	90	19	velocity	velocity	NOUN
ajst-25576	90	20	.	.	PUNCT
ajst-25576	91	1	the	the	DET
ajst-25576	91	2	75	75	NUM
ajst-25576	91	3	steady	steady	ADJ
ajst-25576	91	4	-	-	PUNCT
ajst-25576	91	5	state	state	NOUN
ajst-25576	91	6	error	error	NOUN
ajst-25576	91	7	observed	observe	VERB
ajst-25576	91	8	in	in	ADP
ajst-25576	91	9	the	the	DET
ajst-25576	91	10	refined	refined	ADJ
ajst-25576	91	11	bas	bas	PROPN
ajst-25576	91	12	algorithm	algorithm	NOUN
ajst-25576	91	13	is	be	AUX
ajst-25576	91	14	minimized	minimize	VERB
ajst-25576	91	15	.	.	PUNCT
ajst-25576	92	1	steady	steady	ADJ
ajst-25576	92	2	-	-	PUNCT
ajst-25576	92	3	state	state	NOUN
ajst-25576	92	4	error	error	NOUN
ajst-25576	92	5	is	be	AUX
ajst-25576	92	6	defined	define	VERB
ajst-25576	92	7	as	as	ADP
ajst-25576	92	8	the	the	DET
ajst-25576	92	9	system	system	NOUN
ajst-25576	92	10	's	's	PART
ajst-25576	92	11	discrepancy	discrepancy	NOUN
ajst-25576	92	12	from	from	ADP
ajst-25576	92	13	the	the	DET
ajst-25576	92	14	anticipated	anticipate	VERB
ajst-25576	92	15	value	value	NOUN
ajst-25576	92	16	following	follow	VERB
ajst-25576	92	17	the	the	DET
ajst-25576	92	18	attainment	attainment	NOUN
ajst-25576	92	19	of	of	ADP
ajst-25576	92	20	steady	steady	ADJ
ajst-25576	92	21	state	state	NOUN
ajst-25576	92	22	.	.	PUNCT
ajst-25576	93	1	a	a	DET
ajst-25576	93	2	reduced	reduce	VERB
ajst-25576	93	3	steady	steady	ADJ
ajst-25576	93	4	-	-	PUNCT
ajst-25576	93	5	state	state	NOUN
ajst-25576	93	6	error	error	NOUN
ajst-25576	93	7	signifies	signify	VERB
ajst-25576	93	8	elevated	elevate	VERB
ajst-25576	93	9	control	control	NOUN
ajst-25576	93	10	precision	precision	NOUN
ajst-25576	93	11	,	,	PUNCT
ajst-25576	93	12	enabling	enable	VERB
ajst-25576	93	13	the	the	DET
ajst-25576	93	14	system	system	NOUN
ajst-25576	93	15	to	to	PART
ajst-25576	93	16	cater	cater	VERB
ajst-25576	93	17	to	to	ADP
ajst-25576	93	18	more	more	ADV
ajst-25576	93	19	exacting	exacting	ADJ
ajst-25576	93	20	control	control	NOUN
ajst-25576	93	21	specifications	specification	NOUN
ajst-25576	93	22	.	.	PUNCT
ajst-25576	94	1	compared	compare	VERB
ajst-25576	94	2	with	with	ADP
ajst-25576	94	3	the	the	DET
ajst-25576	94	4	traditional	traditional	ADJ
ajst-25576	94	5	pid	pid	NOUN
ajst-25576	94	6	controller	controller	NOUN
ajst-25576	94	7	,	,	PUNCT
ajst-25576	94	8	the	the	DET
ajst-25576	94	9	improved	improved	ADJ
ajst-25576	94	10	bas	bas	PROPN
ajst-25576	94	11	algorithm	algorithm	NOUN
ajst-25576	94	12	has	have	VERB
ajst-25576	94	13	obvious	obvious	ADJ
ajst-25576	94	14	advantages	advantage	NOUN
ajst-25576	94	15	,	,	PUNCT
ajst-25576	94	16	such	such	ADJ
ajst-25576	94	17	as	as	ADP
ajst-25576	94	18	lower	low	ADJ
ajst-25576	94	19	objective	objective	ADJ
ajst-25576	94	20	function	function	NOUN
ajst-25576	94	21	value	value	NOUN
ajst-25576	94	22	,	,	PUNCT
ajst-25576	94	23	smaller	small	ADJ
ajst-25576	94	24	overshoot	overshoot	NOUN
ajst-25576	94	25	,	,	PUNCT
ajst-25576	94	26	shorter	short	ADJ
ajst-25576	94	27	adjustment	adjustment	NOUN
ajst-25576	94	28	time	time	NOUN
ajst-25576	94	29	and	and	CCONJ
ajst-25576	94	30	smaller	small	ADJ
ajst-25576	94	31	steady	steady	ADJ
ajst-25576	94	32	-	-	PUNCT
ajst-25576	94	33	state	state	NOUN
ajst-25576	94	34	error	error	NOUN
ajst-25576	94	35	.	.	PUNCT
ajst-25576	95	1	this	this	DET
ajst-25576	95	2	algorithm	algorithm	NOUN
ajst-25576	95	3	not	not	PART
ajst-25576	95	4	only	only	ADV
ajst-25576	95	5	keeps	keep	VERB
ajst-25576	95	6	the	the	DET
ajst-25576	95	7	simplicity	simplicity	NOUN
ajst-25576	95	8	of	of	ADP
ajst-25576	95	9	traditional	traditional	ADJ
ajst-25576	95	10	bas	bas	PROPN
ajst-25576	95	11	algorithm	algorithm	NOUN
ajst-25576	95	12	,	,	PUNCT
ajst-25576	95	13	but	but	CCONJ
ajst-25576	95	14	also	also	ADV
ajst-25576	95	15	significantly	significantly	ADV
ajst-25576	95	16	improves	improve	VERB
ajst-25576	95	17	the	the	DET
ajst-25576	95	18	global	global	ADJ
ajst-25576	95	19	optimization	optimization	NOUN
ajst-25576	95	20	ability	ability	NOUN
ajst-25576	95	21	and	and	CCONJ
ajst-25576	95	22	convergence	convergence	NOUN
ajst-25576	95	23	speed	speed	NOUN
ajst-25576	95	24	by	by	ADP
ajst-25576	95	25	introducing	introduce	VERB
ajst-25576	95	26	dynamic	dynamic	ADJ
ajst-25576	95	27	step	step	NOUN
ajst-25576	95	28	adjustment	adjustment	NOUN
ajst-25576	95	29	,	,	PUNCT
ajst-25576	95	30	random	random	ADJ
ajst-25576	95	31	disturbance	disturbance	NOUN
ajst-25576	95	32	and	and	CCONJ
ajst-25576	95	33	elite	elite	ADJ
ajst-25576	95	34	reservation	reservation	NOUN
ajst-25576	95	35	strategy	strategy	NOUN
ajst-25576	95	36	.	.	PUNCT
ajst-25576	96	1	therefore	therefore	ADV
ajst-25576	96	2	,	,	PUNCT
ajst-25576	96	3	the	the	DET
ajst-25576	96	4	improved	improved	ADJ
ajst-25576	96	5	bas	bas	PROPN
ajst-25576	96	6	algorithm	algorithm	NOUN
ajst-25576	96	7	is	be	AUX
ajst-25576	96	8	expected	expect	VERB
ajst-25576	96	9	to	to	PART
ajst-25576	96	10	provide	provide	VERB
ajst-25576	96	11	new	new	ADJ
ajst-25576	96	12	ideas	idea	NOUN
ajst-25576	96	13	and	and	CCONJ
ajst-25576	96	14	methods	method	NOUN
ajst-25576	96	15	for	for	ADP
ajst-25576	96	16	the	the	DET
ajst-25576	96	17	optimization	optimization	NOUN
ajst-25576	96	18	of	of	ADP
ajst-25576	96	19	industrial	industrial	ADJ
ajst-25576	96	20	control	control	NOUN
ajst-25576	96	21	systems	system	NOUN
ajst-25576	96	22	.	.	PUNCT
ajst-25576	97	1	5	5	X
ajst-25576	97	2	.	.	X
ajst-25576	97	3	conclusion	conclusion	NOUN
ajst-25576	97	4	by	by	ADP
ajst-25576	97	5	dynamically	dynamically	ADV
ajst-25576	97	6	adjusting	adjust	VERB
ajst-25576	97	7	the	the	DET
ajst-25576	97	8	step	step	NOUN
ajst-25576	97	9	size	size	NOUN
ajst-25576	97	10	,	,	PUNCT
ajst-25576	97	11	introducing	introduce	VERB
ajst-25576	97	12	random	random	ADJ
ajst-25576	97	13	disturbance	disturbance	NOUN
ajst-25576	97	14	and	and	CCONJ
ajst-25576	97	15	elite	elite	ADJ
ajst-25576	97	16	retention	retention	NOUN
ajst-25576	97	17	strategy	strategy	NOUN
ajst-25576	97	18	,	,	PUNCT
ajst-25576	97	19	the	the	DET
ajst-25576	97	20	improved	improved	ADJ
ajst-25576	97	21	bas	bas	PROPN
ajst-25576	97	22	algorithm	algorithm	NOUN
ajst-25576	97	23	significantly	significantly	ADV
ajst-25576	97	24	improves	improve	VERB
ajst-25576	97	25	the	the	DET
ajst-25576	97	26	global	global	ADJ
ajst-25576	97	27	optimization	optimization	NOUN
ajst-25576	97	28	ability	ability	NOUN
ajst-25576	97	29	and	and	CCONJ
ajst-25576	97	30	convergence	convergence	NOUN
ajst-25576	97	31	speed	speed	NOUN
ajst-25576	97	32	,	,	PUNCT
ajst-25576	97	33	while	while	SCONJ
ajst-25576	97	34	maintaining	maintain	VERB
ajst-25576	97	35	the	the	DET
ajst-25576	97	36	simplicity	simplicity	NOUN
ajst-25576	97	37	of	of	ADP
ajst-25576	97	38	the	the	DET
ajst-25576	97	39	algorithm	algorithm	NOUN
ajst-25576	97	40	.	.	PUNCT
ajst-25576	98	1	simulation	simulation	NOUN
ajst-25576	98	2	results	result	NOUN
ajst-25576	98	3	show	show	VERB
ajst-25576	98	4	that	that	SCONJ
ajst-25576	98	5	compared	compare	VERB
ajst-25576	98	6	with	with	ADP
ajst-25576	98	7	traditional	traditional	ADJ
ajst-25576	98	8	methods	method	NOUN
ajst-25576	98	9	,	,	PUNCT
ajst-25576	98	10	the	the	DET
ajst-25576	98	11	improved	improved	ADJ
ajst-25576	98	12	bas	bas	PROPN
ajst-25576	98	13	algorithm	algorithm	NOUN
ajst-25576	98	14	shows	show	VERB
ajst-25576	98	15	faster	fast	ADJ
ajst-25576	98	16	initial	initial	ADJ
ajst-25576	98	17	convergence	convergence	NOUN
ajst-25576	98	18	speed	speed	NOUN
ajst-25576	98	19	and	and	CCONJ
ajst-25576	98	20	lower	low	ADJ
ajst-25576	98	21	objective	objective	ADJ
ajst-25576	98	22	function	function	NOUN
ajst-25576	98	23	value	value	NOUN
ajst-25576	98	24	in	in	ADP
ajst-25576	98	25	pid	pid	NOUN
ajst-25576	98	26	parameter	parameter	NOUN
ajst-25576	98	27	tuning	tuning	NOUN
ajst-25576	98	28	,	,	PUNCT
ajst-25576	98	29	which	which	PRON
ajst-25576	98	30	means	mean	VERB
ajst-25576	98	31	smaller	small	ADJ
ajst-25576	98	32	overshoot	overshoot	NOUN
ajst-25576	98	33	,	,	PUNCT
ajst-25576	98	34	shorter	short	ADJ
ajst-25576	98	35	adjustment	adjustment	NOUN
ajst-25576	98	36	time	time	NOUN
ajst-25576	98	37	and	and	CCONJ
ajst-25576	98	38	smaller	small	ADJ
ajst-25576	98	39	steady	steady	ADJ
ajst-25576	98	40	-	-	PUNCT
ajst-25576	98	41	state	state	NOUN
ajst-25576	98	42	error	error	NOUN
ajst-25576	98	43	.	.	PUNCT
ajst-25576	99	1	these	these	DET
ajst-25576	99	2	results	result	NOUN
ajst-25576	99	3	confirm	confirm	VERB
ajst-25576	99	4	the	the	DET
ajst-25576	99	5	effectiveness	effectiveness	NOUN
ajst-25576	99	6	and	and	CCONJ
ajst-25576	99	7	potential	potential	NOUN
ajst-25576	99	8	of	of	ADP
ajst-25576	99	9	the	the	DET
ajst-25576	99	10	improved	improve	VERB
ajst-25576	99	11	bas	bas	PROPN
ajst-25576	99	12	algorithm	algorithm	NOUN
ajst-25576	99	13	in	in	ADP
ajst-25576	99	14	industrial	industrial	ADJ
ajst-25576	99	15	control	control	NOUN
ajst-25576	99	16	system	system	NOUN
ajst-25576	99	17	optimization	optimization	NOUN
ajst-25576	99	18	,	,	PUNCT
ajst-25576	99	19	and	and	CCONJ
ajst-25576	99	20	provide	provide	VERB
ajst-25576	99	21	an	an	DET
ajst-25576	99	22	efficient	efficient	ADJ
ajst-25576	99	23	and	and	CCONJ
ajst-25576	99	24	stable	stable	ADJ
ajst-25576	99	25	parameter	parameter	NOUN
ajst-25576	99	26	optimization	optimization	NOUN
ajst-25576	99	27	approach	approach	NOUN
ajst-25576	99	28	for	for	ADP
ajst-25576	99	29	future	future	ADJ
ajst-25576	99	30	control	control	NOUN
ajst-25576	99	31	system	system	NOUN
ajst-25576	99	32	design	design	NOUN
ajst-25576	99	33	.	.	PUNCT
ajst-25576	100	1	references	reference	NOUN
ajst-25576	100	2	[	[	X
ajst-25576	100	3	1	1	NUM
ajst-25576	100	4	]	]	X
ajst-25576	100	5	chu	chu	PROPN
ajst-25576	100	6	,	,	PUNCT
ajst-25576	100	7	p	p	X
ajst-25576	100	8	,	,	PUNCT
ajst-25576	100	9	yu	yu	PROPN
ajst-25576	100	10	,	,	PUNCT
ajst-25576	100	11	y.	y.	PROPN
ajst-25576	100	12	,	,	PUNCT
ajst-25576	100	13	dong	dong	PROPN
ajst-25576	100	14	,	,	PUNCT
ajst-25576	100	15	d.	d.	PROPN
ajst-25576	100	16	,	,	PUNCT
ajst-25576	100	17	lin	lin	PROPN
ajst-25576	100	18	,	,	PUNCT
ajst-25576	100	19	h.	h.	PROPN
ajst-25576	100	20	,	,	PUNCT
ajst-25576	100	21	&	&	CCONJ
ajst-25576	100	22	yuan	yuan	PROPN
ajst-25576	100	23	,	,	PUNCT
ajst-25576	100	24	j.	j.	PROPN
ajst-25576	100	25	(	(	PUNCT
ajst-25576	100	26	2020	2020	NUM
ajst-25576	100	27	)	)	PUNCT
ajst-25576	100	28	.	.	PUNCT
ajst-25576	101	1	nsgaii	nsgaii	NOUN
ajst-25576	101	2	-	-	PUNCT
ajst-25576	101	3	based	base	VERB
ajst-25576	101	4	parameter	parameter	NOUN
ajst-25576	101	5	tuning	tuning	NOUN
ajst-25576	101	6	method	method	NOUN
ajst-25576	101	7	and	and	CCONJ
ajst-25576	101	8	gm	gm	PROPN
ajst-25576	101	9	(	(	PUNCT
ajst-25576	101	10	1,1)-based	1,1)-based	NUM
ajst-25576	101	11	development	development	NOUN
ajst-25576	101	12	of	of	ADP
ajst-25576	101	13	fuzzy	fuzzy	ADJ
ajst-25576	101	14	immune	immune	ADJ
ajst-25576	101	15	pid	pid	NOUN
ajst-25576	101	16	controller	controller	NOUN
ajst-25576	101	17	for	for	ADP
ajst-25576	101	18	automatic	automatic	ADJ
ajst-25576	101	19	train	train	NOUN
ajst-25576	101	20	operation	operation	NOUN
ajst-25576	101	21	system	system	NOUN
ajst-25576	101	22	.	.	PUNCT
ajst-25576	102	1	mathematical	mathematical	ADJ
ajst-25576	102	2	problems	problem	NOUN
ajst-25576	102	3	in	in	ADP
ajst-25576	102	4	engineering	engineering	NOUN
ajst-25576	102	5	,	,	PUNCT
ajst-25576	102	6	2020(6	2020(6	NOUN
ajst-25576	102	7	)	)	PUNCT
ajst-25576	102	8	,	,	PUNCT
ajst-25576	102	9	1	1	NUM
ajst-25576	102	10	-	-	SYM
ajst-25576	102	11	20	20	NUM
ajst-25576	102	12	.	.	PUNCT
ajst-25576	103	1	[	[	X
ajst-25576	103	2	2	2	NUM
ajst-25576	103	3	]	]	X
ajst-25576	103	4	wakitani	wakitani	X
ajst-25576	103	5	,	,	PUNCT
ajst-25576	103	6	s.	s.	PROPN
ajst-25576	103	7	,	,	PUNCT
ajst-25576	103	8	yamamoto	yamamoto	NOUN
ajst-25576	103	9	,	,	PUNCT
ajst-25576	103	10	t.	t.	PROPN
ajst-25576	103	11	,	,	PUNCT
ajst-25576	103	12	&	&	CCONJ
ajst-25576	103	13	gopaluni	gopaluni	PROPN
ajst-25576	103	14	,	,	PUNCT
ajst-25576	103	15	b.	b.	PROPN
ajst-25576	103	16	(	(	PUNCT
ajst-25576	103	17	2019	2019	NUM
ajst-25576	103	18	)	)	PUNCT
ajst-25576	103	19	.	.	PUNCT
ajst-25576	104	1	design	design	NOUN
ajst-25576	104	2	and	and	CCONJ
ajst-25576	104	3	application	application	NOUN
ajst-25576	104	4	of	of	ADP
ajst-25576	104	5	a	a	DET
ajst-25576	104	6	database	database	NOUN
ajst-25576	104	7	-	-	PUNCT
ajst-25576	104	8	driven	drive	VERB
ajst-25576	104	9	pid	pid	NOUN
ajst-25576	104	10	controller	controller	NOUN
ajst-25576	104	11	with	with	ADP
ajst-25576	104	12	datadriven	datadriven	ADJ
ajst-25576	104	13	updating	update	VERB
ajst-25576	104	14	algorithm	algorithm	NOUN
ajst-25576	104	15	.	.	PUNCT
ajst-25576	105	1	industrial	industrial	ADJ
ajst-25576	105	2	and	and	CCONJ
ajst-25576	105	3	engineering	engineer	VERB
ajst-25576	105	4	chemistry	chemistry	NOUN
ajst-25576	105	5	research	research	NOUN
ajst-25576	105	6	,	,	PUNCT
ajst-25576	105	7	58(26	58(26	NUM
ajst-25576	105	8	)	)	PUNCT
ajst-25576	105	9	,	,	PUNCT
ajst-25576	105	10	11419	11419	NUM
ajst-25576	105	11	-	-	SYM
ajst-25576	105	12	11429	11429	NUM
ajst-25576	105	13	.	.	PUNCT
ajst-25576	106	1	[	[	X
ajst-25576	106	2	3	3	NUM
ajst-25576	106	3	]	]	X
ajst-25576	106	4	berkenkamp	berkenkamp	NOUN
ajst-25576	106	5	,	,	PUNCT
ajst-25576	106	6	f.	f.	PROPN
ajst-25576	106	7	,	,	PUNCT
ajst-25576	106	8	krause	krause	PROPN
ajst-25576	106	9	,	,	PUNCT
ajst-25576	106	10	a.	a.	NOUN
ajst-25576	106	11	,	,	PUNCT
ajst-25576	106	12	&	&	CCONJ
ajst-25576	106	13	schoellig	schoellig	PROPN
ajst-25576	106	14	,	,	PUNCT
ajst-25576	106	15	a.	a.	NOUN
ajst-25576	106	16	p.	p.	NOUN
ajst-25576	106	17	(	(	PUNCT
ajst-25576	106	18	2023	2023	NUM
ajst-25576	106	19	)	)	PUNCT
ajst-25576	106	20	.	.	PUNCT
ajst-25576	107	1	bayesian	bayesian	NOUN
ajst-25576	107	2	optimization	optimization	NOUN
ajst-25576	107	3	with	with	ADP
ajst-25576	107	4	safety	safety	NOUN
ajst-25576	107	5	constraints	constraint	NOUN
ajst-25576	107	6	:	:	PUNCT
ajst-25576	107	7	safe	safe	ADJ
ajst-25576	107	8	and	and	CCONJ
ajst-25576	107	9	automatic	automatic	ADJ
ajst-25576	107	10	parameter	parameter	NOUN
ajst-25576	107	11	tuning	tuning	NOUN
ajst-25576	107	12	in	in	ADP
ajst-25576	107	13	robotics	robotic	NOUN
ajst-25576	107	14	.	.	PUNCT
ajst-25576	108	1	machine	machine	NOUN
ajst-25576	108	2	learning	learning	PROPN
ajst-25576	108	3	,	,	PUNCT
ajst-25576	108	4	112(10	112(10	NUM
ajst-25576	108	5	)	)	PUNCT
ajst-25576	108	6	,	,	PUNCT
ajst-25576	108	7	3713	3713	NUM
ajst-25576	108	8	-	-	SYM
ajst-25576	108	9	3747	3747	NUM
ajst-25576	108	10	.	.	PUNCT
ajst-25576	109	1	[	[	X
ajst-25576	109	2	4	4	NUM
ajst-25576	109	3	]	]	X
ajst-25576	109	4	paynter	paynter	PROPN
ajst-25576	109	5	,	,	PUNCT
ajst-25576	109	6	a	a	PRON
ajst-25576	109	7	,	,	PUNCT
ajst-25576	109	8	&	&	CCONJ
ajst-25576	109	9	willis	willis	PROPN
ajst-25576	109	10	,	,	PUNCT
ajst-25576	109	11	a.	a.	PROPN
ajst-25576	109	12	d.	d.	PROPN
ajst-25576	109	13	(	(	PUNCT
ajst-25576	109	14	2021	2021	NUM
ajst-25576	109	15	)	)	PUNCT
ajst-25576	109	16	.	.	PUNCT
ajst-25576	110	1	tuning	tune	VERB
ajst-25576	110	2	parameter	parameter	NOUN
ajst-25576	110	3	selection	selection	NOUN
ajst-25576	110	4	for	for	ADP
ajst-25576	110	5	a	a	DET
ajst-25576	110	6	penalized	penalize	VERB
ajst-25576	110	7	estimator	estimator	NOUN
ajst-25576	110	8	of	of	ADP
ajst-25576	110	9	species	specie	NOUN
ajst-25576	110	10	richness	richness	NOUN
ajst-25576	110	11	.	.	PUNCT
ajst-25576	111	1	journal	journal	NOUN
ajst-25576	111	2	of	of	ADP
ajst-25576	111	3	applied	applied	ADJ
ajst-25576	111	4	statistics	statistic	NOUN
ajst-25576	111	5	,	,	PUNCT
ajst-25576	111	6	48(6	48(6	NOUN
ajst-25576	111	7	)	)	PUNCT
ajst-25576	111	8	,	,	PUNCT
ajst-25576	111	9	1053	1053	NUM
ajst-25576	111	10	-	-	SYM
ajst-25576	111	11	1070	1070	NUM
ajst-25576	111	12	.	.	PUNCT
ajst-25576	112	1	[	[	X
ajst-25576	112	2	5	5	NUM
ajst-25576	112	3	]	]	PUNCT
ajst-25576	112	4	sugasawa	sugasawa	PROPN
ajst-25576	112	5	,	,	PUNCT
ajst-25576	112	6	s.	s.	PROPN
ajst-25576	112	7	,	,	PUNCT
ajst-25576	112	8	&	&	CCONJ
ajst-25576	112	9	yonekura	yonekura	PROPN
ajst-25576	112	10	,	,	PUNCT
ajst-25576	112	11	s.	s.	PROPN
ajst-25576	112	12	(	(	PUNCT
ajst-25576	112	13	2021	2021	NUM
ajst-25576	112	14	)	)	PUNCT
ajst-25576	112	15	.	.	PUNCT
ajst-25576	113	1	on	on	ADP
ajst-25576	113	2	selection	selection	NOUN
ajst-25576	113	3	criteria	criterion	NOUN
ajst-25576	113	4	for	for	ADP
ajst-25576	113	5	the	the	DET
ajst-25576	113	6	tuning	tuning	NOUN
ajst-25576	113	7	parameter	parameter	NOUN
ajst-25576	113	8	in	in	ADP
ajst-25576	113	9	robust	robust	ADJ
ajst-25576	113	10	divergence	divergence	NOUN
ajst-25576	113	11	.	.	PUNCT
ajst-25576	114	1	entropy	entropy	PROPN
ajst-25576	114	2	,	,	PUNCT
ajst-25576	114	3	23(9	23(9	NUM
ajst-25576	114	4	)	)	PUNCT
ajst-25576	114	5	,	,	PUNCT
ajst-25576	114	6	1147	1147	NUM
ajst-25576	114	7	.	.	PUNCT
ajst-25576	115	1	[	[	X
ajst-25576	115	2	6	6	NUM
ajst-25576	115	3	]	]	X
ajst-25576	115	4	zemouche	zemouche	PROPN
ajst-25576	115	5	,	,	PUNCT
ajst-25576	115	6	a.	a.	PROPN
ajst-25576	115	7	,	,	PUNCT
ajst-25576	115	8	zhang	zhang	PROPN
ajst-25576	115	9	,	,	PUNCT
ajst-25576	115	10	f.	f.	PROPN
ajst-25576	115	11	,	,	PUNCT
ajst-25576	115	12	mazenc	mazenc	PROPN
ajst-25576	115	13	,	,	PUNCT
ajst-25576	115	14	f.	f.	PROPN
ajst-25576	115	15	,	,	PUNCT
ajst-25576	115	16	&	&	CCONJ
ajst-25576	115	17	rajamani	rajamani	PROPN
ajst-25576	115	18	,	,	PUNCT
ajst-25576	115	19	r.	r.	PROPN
ajst-25576	115	20	(	(	PUNCT
ajst-25576	115	21	2019	2019	NUM
ajst-25576	115	22	)	)	PUNCT
ajst-25576	115	23	.	.	PUNCT
ajst-25576	116	1	high	high	ADJ
ajst-25576	116	2	-	-	PUNCT
ajst-25576	116	3	gain	gain	NOUN
ajst-25576	116	4	nonlinear	nonlinear	ADJ
ajst-25576	116	5	observer	observer	NOUN
ajst-25576	116	6	with	with	ADP
ajst-25576	116	7	lower	low	ADJ
ajst-25576	116	8	tuning	tuning	NOUN
ajst-25576	116	9	parameter	parameter	NOUN
ajst-25576	116	10	.	.	PUNCT
ajst-25576	117	1	ieee	ieee	NOUN
ajst-25576	117	2	transactions	transaction	NOUN
ajst-25576	117	3	on	on	ADP
ajst-25576	117	4	automatic	automatic	ADJ
ajst-25576	117	5	control	control	NOUN
ajst-25576	117	6	,	,	PUNCT
ajst-25576	117	7	64(8	64(8	NOUN
ajst-25576	117	8	)	)	PUNCT
ajst-25576	117	9	,	,	PUNCT
ajst-25576	117	10	3194	3194	NUM
ajst-25576	117	11	-	-	SYM
ajst-25576	117	12	3209	3209	NUM
ajst-25576	117	13	.	.	PUNCT
ajst-25576	118	1	[	[	X
ajst-25576	118	2	7	7	NUM
ajst-25576	118	3	]	]	X
ajst-25576	118	4	taveira	taveira	PROPN
ajst-25576	118	5	,	,	PUNCT
ajst-25576	118	6	l.	l.	PROPN
ajst-25576	118	7	f.	f.	PROPN
ajst-25576	118	8	r.	r.	PROPN
ajst-25576	118	9	,	,	PUNCT
ajst-25576	118	10	kurc	kurc	NOUN
ajst-25576	118	11	,	,	PUNCT
ajst-25576	118	12	t.	t.	PROPN
ajst-25576	118	13	,	,	PUNCT
ajst-25576	118	14	melo	melo	PROPN
ajst-25576	118	15	,	,	PUNCT
ajst-25576	118	16	a.	a.	PROPN
ajst-25576	118	17	c.	c.	PROPN
ajst-25576	118	18	m.	m.	PROPN
ajst-25576	118	19	a.	a.	PROPN
ajst-25576	118	20	,	,	PUNCT
ajst-25576	118	21	kong	kong	PROPN
ajst-25576	118	22	,	,	PUNCT
ajst-25576	118	23	j.	j.	PROPN
ajst-25576	118	24	,	,	PUNCT
ajst-25576	118	25	bremer	bremer	NOUN
ajst-25576	118	26	,	,	PUNCT
ajst-25576	118	27	e.	e.	PROPN
ajst-25576	118	28	,	,	PUNCT
ajst-25576	118	29	&	&	CCONJ
ajst-25576	118	30	saltz	saltz	PROPN
ajst-25576	118	31	,	,	PUNCT
ajst-25576	118	32	j.	j.	PROPN
ajst-25576	118	33	h.	h.	PROPN
ajst-25576	118	34	,	,	PUNCT
ajst-25576	118	35	et	et	PROPN
ajst-25576	118	36	al	al	PROPN
ajst-25576	118	37	.	.	PROPN
ajst-25576	119	1	(	(	PUNCT
ajst-25576	119	2	2019	2019	NUM
ajst-25576	119	3	)	)	PUNCT
ajst-25576	119	4	.	.	PUNCT
ajst-25576	120	1	multi	multi	ADJ
ajst-25576	120	2	-	-	ADJ
ajst-25576	120	3	objective	objective	ADJ
ajst-25576	120	4	parameter	parameter	NOUN
ajst-25576	120	5	auto	auto	NOUN
ajst-25576	120	6	-	-	PUNCT
ajst-25576	120	7	tuning	tuning	NOUN
ajst-25576	120	8	for	for	ADP
ajst-25576	120	9	tissue	tissue	NOUN
ajst-25576	120	10	image	image	NOUN
ajst-25576	120	11	segmentation	segmentation	NOUN
ajst-25576	120	12	workflows	workflow	NOUN
ajst-25576	120	13	.	.	PUNCT
ajst-25576	121	1	journal	journal	PROPN
ajst-25576	121	2	of	of	ADP
ajst-25576	121	3	digital	digital	ADJ
ajst-25576	121	4	imaging	imaging	NOUN
ajst-25576	121	5	,	,	PUNCT
ajst-25576	121	6	32(3	32(3	NUM
ajst-25576	121	7	)	)	PUNCT
ajst-25576	121	8	,	,	PUNCT
ajst-25576	121	9	521	521	NUM
ajst-25576	121	10	-	-	SYM
ajst-25576	121	11	533	533	NUM
ajst-25576	121	12	.	.	PUNCT
ajst-25576	122	1	[	[	X
ajst-25576	122	2	8	8	NUM
ajst-25576	122	3	]	]	X
ajst-25576	122	4	fuyin	fuyin	NOUN
ajst-25576	122	5	,	,	PUNCT
ajst-25576	122	6	n.	n.	PROPN
ajst-25576	122	7	i.	i.	PROPN
ajst-25576	122	8	,	,	PUNCT
ajst-25576	122	9	&	&	CCONJ
ajst-25576	122	10	jian	jian	PROPN
ajst-25576	122	11	,	,	PUNCT
ajst-25576	122	12	h.	h.	PROPN
ajst-25576	122	13	(	(	PUNCT
ajst-25576	122	14	2024	2024	NUM
ajst-25576	122	15	)	)	PUNCT
ajst-25576	122	16	.	.	PUNCT
ajst-25576	123	1	research	research	NOUN
ajst-25576	123	2	on	on	ADP
ajst-25576	123	3	upqc	upqc	PROPN
ajst-25576	123	4	harmonic	harmonic	PROPN
ajst-25576	123	5	control	control	NOUN
ajst-25576	123	6	strategy	strategy	NOUN
ajst-25576	123	7	based	base	VERB
ajst-25576	123	8	on	on	ADP
ajst-25576	123	9	optimized	optimize	VERB
ajst-25576	123	10	qpir	qpir	NOUN
ajst-25576	123	11	controller	controller	NOUN
ajst-25576	123	12	of	of	ADP
ajst-25576	123	13	beetle	beetle	NOUN
ajst-25576	123	14	antennae	antennae	NOUN
ajst-25576	123	15	search	search	NOUN
ajst-25576	123	16	algorithm	algorithm	NOUN
ajst-25576	123	17	in	in	ADP
ajst-25576	123	18	microgrid	microgrid	NOUN
ajst-25576	123	19	.	.	PUNCT
ajst-25576	124	1	electrical	electrical	ADJ
ajst-25576	124	2	engineering	engineering	NOUN
ajst-25576	124	3	,	,	PUNCT
ajst-25576	124	4	106(3	106(3	NUM
ajst-25576	124	5	)	)	PUNCT
ajst-25576	124	6	,	,	PUNCT
ajst-25576	124	7	2357	2357	NUM
ajst-25576	124	8	-	-	SYM
ajst-25576	124	9	2369	2369	NUM
ajst-25576	124	10	.	.	PUNCT