id	sid	tid	token	lemma	pos
fcis-30730	1	1	frontiers	frontier	NOUN
fcis-30730	1	2	in	in	ADP
fcis-30730	1	3	computing	computing	NOUN
fcis-30730	1	4	and	and	CCONJ
fcis-30730	1	5	intelligent	intelligent	ADJ
fcis-30730	1	6	systems	system	NOUN
fcis-30730	1	7	issn	issn	VERB
fcis-30730	1	8	:	:	PUNCT
fcis-30730	1	9	2832	2832	NUM
fcis-30730	1	10	-	-	SYM
fcis-30730	1	11	6024	6024	NUM
fcis-30730	1	12	|	|	NOUN
fcis-30730	1	13	vol	vol	NOUN
fcis-30730	1	14	.	.	PROPN
fcis-30730	2	1	12	12	NUM
fcis-30730	2	2	,	,	PUNCT
fcis-30730	2	3	no	no	INTJ
fcis-30730	2	4	.	.	NOUN
fcis-30730	2	5	2	2	NUM
fcis-30730	2	6	,	,	PUNCT
fcis-30730	2	7	2025	2025	NUM
fcis-30730	2	8	6	6	NUM
fcis-30730	2	9	penelitian	penelitian	PROPN
fcis-30730	2	10	tentang	tentang	PROPN
fcis-30730	2	11	kontrol	kontrol	PROPN
fcis-30730	2	12	heading	heading	PROPN
fcis-30730	2	13	berdasarkan	berdasarkan	PROPN
fcis-30730	2	14	pid	pid	PROPN
fcis-30730	3	1	neural	neural	ADJ
fcis-30730	3	2	fuzzy	fuzzy	PROPN
fcis-30730	3	3	jie	jie	PROPN
fcis-30730	3	4	wang	wang	PROPN
fcis-30730	3	5	*	*	PUNCT
fcis-30730	3	6	school	school	NOUN
fcis-30730	3	7	of	of	ADP
fcis-30730	3	8	mechanical	mechanical	ADJ
fcis-30730	3	9	engineering	engineering	NOUN
fcis-30730	3	10	,	,	PUNCT
fcis-30730	3	11	university	university	PROPN
fcis-30730	3	12	of	of	ADP
fcis-30730	3	13	jinan	jinan	PROPN
fcis-30730	3	14	,	,	PUNCT
fcis-30730	3	15	jinan	jinan	PROPN
fcis-30730	3	16	,	,	PUNCT
fcis-30730	3	17	shandong	shandong	PROPN
fcis-30730	3	18	,	,	PUNCT
fcis-30730	3	19	china	china	PROPN
fcis-30730	3	20	*	*	PUNCT
fcis-30730	3	21	corresponding	correspond	VERB
fcis-30730	3	22	author	author	NOUN
fcis-30730	3	23	email	email	NOUN
fcis-30730	3	24	:	:	PUNCT
fcis-30730	3	25	544452099@qq.com	544452099@qq.com	NUM
fcis-30730	3	26	abstract	abstract	NOUN
fcis-30730	3	27	:	:	PUNCT
fcis-30730	3	28	with	with	ADP
fcis-30730	3	29	the	the	DET
fcis-30730	3	30	continuous	continuous	ADJ
fcis-30730	3	31	advancement	advancement	NOUN
fcis-30730	3	32	of	of	ADP
fcis-30730	3	33	the	the	DET
fcis-30730	3	34	internet	internet	NOUN
fcis-30730	3	35	of	of	ADP
fcis-30730	3	36	everything	everything	PRON
fcis-30730	3	37	era	era	NOUN
fcis-30730	3	38	and	and	CCONJ
fcis-30730	3	39	the	the	DET
fcis-30730	3	40	increasing	increase	VERB
fcis-30730	3	41	cost	cost	NOUN
fcis-30730	3	42	of	of	ADP
fcis-30730	3	43	labor	labor	NOUN
fcis-30730	3	44	,	,	PUNCT
fcis-30730	3	45	the	the	DET
fcis-30730	3	46	aquaculture	aquaculture	NOUN
fcis-30730	3	47	industry	industry	NOUN
fcis-30730	3	48	is	be	AUX
fcis-30730	3	49	undergoing	undergo	VERB
fcis-30730	3	50	intelligent	intelligent	ADJ
fcis-30730	3	51	changes	change	NOUN
fcis-30730	3	52	.	.	PUNCT
fcis-30730	4	1	a	a	DET
fcis-30730	4	2	set	set	NOUN
fcis-30730	4	3	of	of	ADP
fcis-30730	4	4	technical	technical	ADJ
fcis-30730	4	5	solutions	solution	NOUN
fcis-30730	4	6	for	for	ADP
fcis-30730	4	7	heading	head	VERB
fcis-30730	4	8	control	control	NOUN
fcis-30730	4	9	is	be	AUX
fcis-30730	4	10	proposed	propose	VERB
fcis-30730	4	11	to	to	PART
fcis-30730	4	12	introduce	introduce	VERB
fcis-30730	4	13	a	a	DET
fcis-30730	4	14	fuzzy	fuzzy	ADJ
fcis-30730	4	15	neural	neural	ADJ
fcis-30730	4	16	pid	pid	NOUN
fcis-30730	4	17	controller	controller	NOUN
fcis-30730	4	18	to	to	ADP
fcis-30730	4	19	the	the	DET
fcis-30730	4	20	field	field	NOUN
fcis-30730	4	21	of	of	ADP
fcis-30730	4	22	heading	head	VERB
fcis-30730	4	23	control	control	NOUN
fcis-30730	4	24	of	of	ADP
fcis-30730	4	25	kelp	kelp	NOUN
fcis-30730	4	26	harvesting	harvesting	NOUN
fcis-30730	4	27	vessel	vessel	NOUN
fcis-30730	4	28	.	.	PUNCT
fcis-30730	5	1	firstly	firstly	ADV
fcis-30730	5	2	,	,	PUNCT
fcis-30730	5	3	fuzzy	fuzzy	ADJ
fcis-30730	5	4	logic	logic	NOUN
fcis-30730	5	5	and	and	CCONJ
fcis-30730	5	6	neural	neural	ADJ
fcis-30730	5	7	network	network	NOUN
fcis-30730	5	8	technology	technology	NOUN
fcis-30730	5	9	are	be	AUX
fcis-30730	5	10	combined	combine	VERB
fcis-30730	5	11	,	,	PUNCT
fcis-30730	5	12	and	and	CCONJ
fcis-30730	5	13	secondly	secondly	ADV
fcis-30730	5	14	,	,	PUNCT
fcis-30730	5	15	fuzzy	fuzzy	ADJ
fcis-30730	5	16	pid	pid	NOUN
fcis-30730	5	17	,	,	PUNCT
fcis-30730	5	18	fuzzy	fuzzy	ADJ
fcis-30730	5	19	neural	neural	ADJ
fcis-30730	5	20	pid	pid	NOUN
fcis-30730	5	21	control	control	PROPN
fcis-30730	5	22	strategy	strategy	NOUN
fcis-30730	5	23	model	model	NOUN
fcis-30730	5	24	and	and	CCONJ
fcis-30730	5	25	heading	head	VERB
fcis-30730	5	26	control	control	NOUN
fcis-30730	5	27	model	model	NOUN
fcis-30730	5	28	are	be	AUX
fcis-30730	5	29	designed	design	VERB
fcis-30730	5	30	through	through	ADP
fcis-30730	5	31	simulink	simulink	PROPN
fcis-30730	5	32	.	.	PUNCT
fcis-30730	6	1	through	through	ADP
fcis-30730	6	2	the	the	DET
fcis-30730	6	3	simulation	simulation	NOUN
fcis-30730	6	4	results	result	NOUN
fcis-30730	6	5	,	,	PUNCT
fcis-30730	6	6	it	it	PRON
fcis-30730	6	7	is	be	AUX
fcis-30730	6	8	found	find	VERB
fcis-30730	6	9	that	that	SCONJ
fcis-30730	6	10	the	the	DET
fcis-30730	6	11	fuzzy	fuzzy	ADJ
fcis-30730	6	12	neural	neural	ADJ
fcis-30730	6	13	pid	pid	NOUN
fcis-30730	6	14	heading	head	VERB
fcis-30730	6	15	controller	controller	NOUN
fcis-30730	6	16	has	have	VERB
fcis-30730	6	17	small	small	ADJ
fcis-30730	6	18	overshoot	overshoot	NOUN
fcis-30730	6	19	,	,	PUNCT
fcis-30730	6	20	small	small	ADJ
fcis-30730	6	21	static	static	ADJ
fcis-30730	6	22	error	error	NOUN
fcis-30730	6	23	and	and	CCONJ
fcis-30730	6	24	fast	fast	ADJ
fcis-30730	6	25	response	response	NOUN
fcis-30730	6	26	speed	speed	NOUN
fcis-30730	6	27	.	.	PUNCT
fcis-30730	7	1	keywords	keyword	NOUN
fcis-30730	7	2	:	:	PUNCT
fcis-30730	7	3	kelp	kelp	NOUN
fcis-30730	7	4	harvesting	harvesting	NOUN
fcis-30730	7	5	vessel	vessel	NOUN
fcis-30730	7	6	;	;	PUNCT
fcis-30730	7	7	heading	head	VERB
fcis-30730	7	8	control	control	NOUN
fcis-30730	7	9	;	;	PUNCT
fcis-30730	7	10	fuzzy	fuzzy	ADJ
fcis-30730	7	11	neural	neural	ADJ
fcis-30730	7	12	pid	pid	PROPN
fcis-30730	7	13	.	.	PROPN
fcis-30730	7	14	1	1	NUM
fcis-30730	7	15	.	.	X
fcis-30730	7	16	introduction	introduction	NOUN
fcis-30730	7	17	when	when	SCONJ
fcis-30730	7	18	the	the	DET
fcis-30730	7	19	kelp	kelp	NOUN
fcis-30730	7	20	harvesting	harvesting	NOUN
fcis-30730	7	21	vessel	vessel	NOUN
fcis-30730	7	22	is	be	AUX
fcis-30730	7	23	operating	operate	VERB
fcis-30730	7	24	,	,	PUNCT
fcis-30730	7	25	it	it	PRON
fcis-30730	7	26	needs	need	VERB
fcis-30730	7	27	to	to	PART
fcis-30730	7	28	travel	travel	VERB
fcis-30730	7	29	to	to	ADP
fcis-30730	7	30	the	the	DET
fcis-30730	7	31	target	target	NOUN
fcis-30730	7	32	position	position	NOUN
fcis-30730	7	33	in	in	ADP
fcis-30730	7	34	strict	strict	ADJ
fcis-30730	7	35	accordance	accordance	NOUN
fcis-30730	7	36	with	with	ADP
fcis-30730	7	37	the	the	DET
fcis-30730	7	38	planned	planned	ADJ
fcis-30730	7	39	route	route	NOUN
fcis-30730	7	40	,	,	PUNCT
fcis-30730	7	41	and	and	CCONJ
fcis-30730	7	42	the	the	DET
fcis-30730	7	43	ability	ability	NOUN
fcis-30730	7	44	to	to	PART
fcis-30730	7	45	accurately	accurately	ADV
fcis-30730	7	46	control	control	VERB
fcis-30730	7	47	the	the	DET
fcis-30730	7	48	heading	heading	NOUN
fcis-30730	7	49	will	will	AUX
fcis-30730	7	50	be	be	AUX
fcis-30730	7	51	the	the	DET
fcis-30730	7	52	ultimate	ultimate	ADJ
fcis-30730	7	53	goal	goal	NOUN
fcis-30730	7	54	of	of	ADP
fcis-30730	7	55	the	the	DET
fcis-30730	7	56	system	system	NOUN
fcis-30730	7	57	control	control	NOUN
fcis-30730	7	58	.	.	PUNCT
fcis-30730	8	1	the	the	DET
fcis-30730	8	2	heading	head	VERB
fcis-30730	8	3	control	control	NOUN
fcis-30730	8	4	requirements	requirement	NOUN
fcis-30730	8	5	of	of	ADP
fcis-30730	8	6	the	the	DET
fcis-30730	8	7	system	system	NOUN
fcis-30730	8	8	are	be	AUX
fcis-30730	8	9	:	:	PUNCT
fcis-30730	8	10	firstly	firstly	ADV
fcis-30730	8	11	,	,	PUNCT
fcis-30730	8	12	when	when	SCONJ
fcis-30730	8	13	the	the	DET
fcis-30730	8	14	ship	ship	NOUN
fcis-30730	8	15	arrives	arrive	VERB
fcis-30730	8	16	at	at	ADP
fcis-30730	8	17	the	the	DET
fcis-30730	8	18	preset	preset	ADJ
fcis-30730	8	19	steering	steering	NOUN
fcis-30730	8	20	position	position	NOUN
fcis-30730	8	21	,	,	PUNCT
fcis-30730	8	22	it	it	PRON
fcis-30730	8	23	needs	need	VERB
fcis-30730	8	24	to	to	PART
fcis-30730	8	25	realize	realize	VERB
fcis-30730	8	26	fast	fast	ADJ
fcis-30730	8	27	heading	heading	NOUN
fcis-30730	8	28	switching	switching	NOUN
fcis-30730	8	29	,	,	PUNCT
fcis-30730	8	30	and	and	CCONJ
fcis-30730	8	31	the	the	DET
fcis-30730	8	32	controller	controller	NOUN
fcis-30730	8	33	dynamically	dynamically	ADV
fcis-30730	8	34	responds	respond	VERB
fcis-30730	8	35	to	to	PART
fcis-30730	8	36	generate	generate	VERB
fcis-30730	8	37	commands	command	NOUN
fcis-30730	8	38	to	to	PART
fcis-30730	8	39	be	be	AUX
fcis-30730	8	40	inputted	inputte	VERB
fcis-30730	8	41	to	to	ADP
fcis-30730	8	42	the	the	DET
fcis-30730	8	43	actuators	actuator	NOUN
fcis-30730	8	44	.	.	PUNCT
fcis-30730	9	1	secondly	secondly	ADV
fcis-30730	9	2	,	,	PUNCT
fcis-30730	9	3	when	when	SCONJ
fcis-30730	9	4	the	the	DET
fcis-30730	9	5	ship	ship	NOUN
fcis-30730	9	6	is	be	AUX
fcis-30730	9	7	sailing	sail	VERB
fcis-30730	9	8	in	in	ADP
fcis-30730	9	9	a	a	DET
fcis-30730	9	10	straight	straight	ADJ
fcis-30730	9	11	line	line	NOUN
fcis-30730	9	12	,	,	PUNCT
fcis-30730	9	13	the	the	DET
fcis-30730	9	14	system	system	NOUN
fcis-30730	9	15	not	not	PART
fcis-30730	9	16	only	only	ADV
fcis-30730	9	17	has	have	AUX
fcis-30730	9	18	to	to	PART
fcis-30730	9	19	meet	meet	VERB
fcis-30730	9	20	the	the	DET
fcis-30730	9	21	dynamic	dynamic	ADJ
fcis-30730	9	22	response	response	NOUN
fcis-30730	9	23	requirements	requirement	NOUN
fcis-30730	9	24	but	but	CCONJ
fcis-30730	9	25	also	also	ADV
fcis-30730	9	26	has	have	VERB
fcis-30730	9	27	to	to	PART
fcis-30730	9	28	ensure	ensure	VERB
fcis-30730	9	29	the	the	DET
fcis-30730	9	30	stability	stability	NOUN
fcis-30730	9	31	of	of	ADP
fcis-30730	9	32	the	the	DET
fcis-30730	9	33	heading	heading	NOUN
fcis-30730	9	34	,	,	PUNCT
fcis-30730	9	35	and	and	CCONJ
fcis-30730	9	36	too	too	ADV
fcis-30730	9	37	large	large	ADJ
fcis-30730	9	38	a	a	DET
fcis-30730	9	39	deviation	deviation	NOUN
fcis-30730	9	40	in	in	ADP
fcis-30730	9	41	the	the	DET
fcis-30730	9	42	heading	heading	NOUN
fcis-30730	9	43	will	will	AUX
fcis-30730	9	44	lead	lead	VERB
fcis-30730	9	45	to	to	ADP
fcis-30730	9	46	resource	resource	NOUN
fcis-30730	9	47	loss	loss	NOUN
fcis-30730	9	48	;	;	PUNCT
fcis-30730	9	49	finally	finally	ADV
fcis-30730	9	50	,	,	PUNCT
fcis-30730	9	51	if	if	SCONJ
fcis-30730	9	52	the	the	DET
fcis-30730	9	53	control	control	NOUN
fcis-30730	9	54	accuracy	accuracy	NOUN
fcis-30730	9	55	is	be	AUX
fcis-30730	9	56	too	too	ADV
fcis-30730	9	57	harsh	harsh	ADJ
fcis-30730	9	58	,	,	PUNCT
fcis-30730	9	59	the	the	DET
fcis-30730	9	60	power	power	NOUN
fcis-30730	9	61	components	component	NOUN
fcis-30730	9	62	will	will	AUX
fcis-30730	9	63	be	be	AUX
fcis-30730	9	64	changed	change	VERB
fcis-30730	9	65	frequently	frequently	ADV
fcis-30730	9	66	,	,	PUNCT
fcis-30730	9	67	which	which	PRON
fcis-30730	9	68	will	will	AUX
fcis-30730	9	69	also	also	ADV
fcis-30730	9	70	cause	cause	VERB
fcis-30730	9	71	a	a	DET
fcis-30730	9	72	test	test	NOUN
fcis-30730	9	73	of	of	ADP
fcis-30730	9	74	the	the	DET
fcis-30730	9	75	mechanical	mechanical	ADJ
fcis-30730	9	76	durability	durability	NOUN
fcis-30730	9	77	.	.	PUNCT
fcis-30730	10	1	this	this	PRON
fcis-30730	10	2	makes	make	VERB
fcis-30730	10	3	the	the	DET
fcis-30730	10	4	design	design	NOUN
fcis-30730	10	5	of	of	ADP
fcis-30730	10	6	the	the	DET
fcis-30730	10	7	heading	head	VERB
fcis-30730	10	8	controller	controller	NOUN
fcis-30730	10	9	very	very	ADV
fcis-30730	10	10	important	important	ADJ
fcis-30730	10	11	and	and	CCONJ
fcis-30730	10	12	difficult	difficult	ADJ
fcis-30730	10	13	to	to	PART
fcis-30730	10	14	find	find	VERB
fcis-30730	10	15	a	a	DET
fcis-30730	10	16	balance	balance	NOUN
fcis-30730	10	17	between	between	ADP
fcis-30730	10	18	control	control	NOUN
fcis-30730	10	19	accuracy	accuracy	NOUN
fcis-30730	10	20	and	and	CCONJ
fcis-30730	10	21	mechanical	mechanical	ADJ
fcis-30730	10	22	durability	durability	NOUN
fcis-30730	10	23	.	.	PUNCT
fcis-30730	11	1	[	[	X
fcis-30730	11	2	1	1	NUM
fcis-30730	11	3	]	]	SYM
fcis-30730	11	4	2	2	NUM
fcis-30730	11	5	.	.	X
fcis-30730	11	6	fuzzy	fuzzy	ADJ
fcis-30730	11	7	neural	neural	ADJ
fcis-30730	11	8	pid	pid	NOUN
fcis-30730	11	9	controller	controller	NOUN
fcis-30730	11	10	design	design	NOUN
fcis-30730	11	11	δr	δr	NOUN
fcis-30730	11	12	'	'	PART
fcis-30730	11	13	δr	δr	ADP
fcis-30730	11	14	δkp	δkp	PROPN
fcis-30730	11	15	δki	δki	PROPN
fcis-30730	11	16	δkd	δkd	NOUN
fcis-30730	11	17	…	…	PUNCT
fcis-30730	11	18	…	…	PUNCT
fcis-30730	11	19	…	…	PUNCT
fcis-30730	11	20	…	…	PUNCT
fcis-30730	11	21	input	input	NOUN
fcis-30730	11	22	layer	layer	NOUN
fcis-30730	11	23	affinity	affinity	NOUN
fcis-30730	11	24	functions	function	NOUN
fcis-30730	11	25	generatio	generatio	VERB
fcis-30730	11	26	n	n	PRON
fcis-30730	11	27	layer	layer	NOUN
fcis-30730	11	28	fuzzy	fuzzy	ADJ
fcis-30730	11	29	inference	inference	NOUN
fcis-30730	11	30	layer	layer	NOUN
fcis-30730	11	31	normalization	normalization	NOUN
fcis-30730	11	32	layer	layer	NOUN
fcis-30730	11	33	output	output	NOUN
fcis-30730	11	34	layer	layer	NOUN
fcis-30730	11	35	mode	mode	NOUN
fcis-30730	11	36	shun	shun	PROPN
fcis-30730	11	37	communications	communication	NOUN
fcis-30730	11	38	fig	fig	NOUN
fcis-30730	11	39	1	1	NUM
fcis-30730	11	40	.	.	PUNCT
fcis-30730	12	1	fuzzy	fuzzy	ADJ
fcis-30730	12	2	neural	neural	ADJ
fcis-30730	12	3	network	network	NOUN
fcis-30730	12	4	pid	pid	NOUN
fcis-30730	12	5	network	network	NOUN
fcis-30730	12	6	structure	structure	NOUN
fcis-30730	12	7	fuzzy	fuzzy	ADJ
fcis-30730	12	8	neural	neural	ADJ
fcis-30730	12	9	network	network	NOUN
fcis-30730	12	10	pid	pid	NOUN
fcis-30730	12	11	network	network	NOUN
fcis-30730	12	12	structure	structure	NOUN
fcis-30730	12	13	[	[	X
fcis-30730	12	14	2,3,4	2,3,4	NOUN
fcis-30730	12	15	]	]	PUNCT
fcis-30730	12	16	as	as	SCONJ
fcis-30730	12	17	shown	show	VERB
fcis-30730	12	18	in	in	ADP
fcis-30730	12	19	fig	fig	NOUN
fcis-30730	12	20	.	.	PUNCT
fcis-30730	13	1	1	1	NUM
fcis-30730	13	2	,	,	PUNCT
fcis-30730	13	3	the	the	DET
fcis-30730	13	4	structural	structural	ADJ
fcis-30730	13	5	design	design	NOUN
fcis-30730	13	6	of	of	ADP
fcis-30730	13	7	fuzzy	fuzzy	ADJ
fcis-30730	13	8	neural	neural	ADJ
fcis-30730	13	9	network	network	NOUN
fcis-30730	13	10	needs	need	VERB
fcis-30730	13	11	to	to	PART
fcis-30730	13	12	first	first	ADV
fcis-30730	13	13	clarify	clarify	VERB
fcis-30730	13	14	the	the	DET
fcis-30730	13	15	number	number	NOUN
fcis-30730	13	16	of	of	ADP
fcis-30730	13	17	neurons	neuron	NOUN
fcis-30730	13	18	in	in	ADP
fcis-30730	13	19	each	each	DET
fcis-30730	13	20	layer	layer	NOUN
fcis-30730	13	21	and	and	CCONJ
fcis-30730	13	22	its	its	PRON
fcis-30730	13	23	input	input	NOUN
fcis-30730	13	24	-	-	PUNCT
fcis-30730	13	25	output	output	NOUN
fcis-30730	13	26	relationship	relationship	NOUN
fcis-30730	13	27	.	.	PUNCT
fcis-30730	14	1	the	the	DET
fcis-30730	14	2	first	first	ADJ
fcis-30730	14	3	layer	layer	NOUN
fcis-30730	14	4	is	be	AUX
fcis-30730	14	5	the	the	DET
fcis-30730	14	6	input	input	NOUN
fcis-30730	14	7	layer	layer	NOUN
fcis-30730	14	8	,	,	PUNCT
fcis-30730	14	9	which	which	PRON
fcis-30730	14	10	contains	contain	VERB
fcis-30730	14	11	two	two	NUM
fcis-30730	14	12	neuron	neuron	NOUN
fcis-30730	14	13	nodes	node	NOUN
fcis-30730	14	14	with	with	ADP
fcis-30730	14	15	clear	clear	ADJ
fcis-30730	14	16	physical	physical	ADJ
fcis-30730	14	17	significance	significance	NOUN
fcis-30730	14	18	:	:	PUNCT
fcis-30730	14	19	the	the	DET
fcis-30730	14	20	system	system	NOUN
fcis-30730	14	21	deviation	deviation	NOUN
fcis-30730	14	22	e	e	NOUN
fcis-30730	14	23	and	and	CCONJ
fcis-30730	14	24	its	its	PRON
fcis-30730	14	25	rate	rate	NOUN
fcis-30730	14	26	of	of	ADP
fcis-30730	14	27	change	change	NOUN
fcis-30730	14	28	ec	ec	PROPN
fcis-30730	14	29	.	.	PUNCT
fcis-30730	14	30	,	,	PUNCT
fcis-30730	14	31	corresponding	correspond	VERB
fcis-30730	14	32	to	to	ADP
fcis-30730	14	33	the	the	DET
fcis-30730	14	34	number	number	NOUN
fcis-30730	14	35	of	of	ADP
fcis-30730	14	36	input	input	NOUN
fcis-30730	14	37	variables	variable	NOUN
fcis-30730	14	38	n	n	NOUN
fcis-30730	14	39	=	=	SYM
fcis-30730	14	40	2	2	NUM
fcis-30730	14	41	.	.	PUNCT
fcis-30730	15	1	the	the	DET
fcis-30730	15	2	input	input	NOUN
fcis-30730	15	3	-	-	PUNCT
fcis-30730	15	4	output	output	NOUN
fcis-30730	15	5	relationship	relationship	NOUN
fcis-30730	15	6	of	of	ADP
fcis-30730	15	7	this	this	DET
fcis-30730	15	8	layer	layer	NOUN
fcis-30730	15	9	can	can	AUX
fcis-30730	15	10	be	be	AUX
fcis-30730	15	11	expressed	express	VERB
fcis-30730	15	12	as	as	SCONJ
fcis-30730	15	13	follows	follow	VERB
fcis-30730	15	14	:	:	PUNCT
fcis-30730	15	15			NOUN
fcis-30730	15	16	1	1	INTJ
fcis-30730	15	17	if	if	SCONJ
fcis-30730	15	18	i	i	PRON
fcis-30730	15	19	x	x	PUNCT
fcis-30730	16	1	(	(	PUNCT
fcis-30730	16	2	1	1	X
fcis-30730	16	3	)	)	PUNCT
fcis-30730	16	4	the	the	DET
fcis-30730	16	5	second	second	ADJ
fcis-30730	16	6	layer	layer	NOUN
fcis-30730	16	7	is	be	AUX
fcis-30730	16	8	the	the	DET
fcis-30730	16	9	generating	generate	VERB
fcis-30730	16	10	layer	layer	NOUN
fcis-30730	16	11	of	of	ADP
fcis-30730	16	12	the	the	DET
fcis-30730	16	13	affiliation	affiliation	NOUN
fcis-30730	16	14	function	function	NOUN
fcis-30730	16	15	,	,	PUNCT
fcis-30730	16	16	called	call	VERB
fcis-30730	16	17	the	the	DET
fcis-30730	16	18	fuzzification	fuzzification	NOUN
fcis-30730	16	19	layer	layer	NOUN
fcis-30730	16	20	.	.	PUNCT
fcis-30730	17	1	in	in	ADP
fcis-30730	17	2	particular	particular	ADJ
fcis-30730	17	3	,	,	PUNCT
fcis-30730	17	4	this	this	DET
fcis-30730	17	5	layer	layer	NOUN
fcis-30730	17	6	selects	select	VERB
fcis-30730	17	7	the	the	DET
fcis-30730	17	8	affiliation	affiliation	NOUN
fcis-30730	17	9	function	function	NOUN
fcis-30730	17	10	to	to	PART
fcis-30730	17	11	fuzzify	fuzzify	VERB
fcis-30730	17	12	the	the	DET
fcis-30730	17	13	input	input	NOUN
fcis-30730	17	14	variables	variable	NOUN
fcis-30730	17	15	e	e	PROPN
fcis-30730	17	16	and	and	CCONJ
fcis-30730	17	17	ec	ec	PROPN
fcis-30730	17	18	,	,	PUNCT
fcis-30730	17	19	which	which	PRON
fcis-30730	17	20	is	be	AUX
fcis-30730	17	21	mathematically	mathematically	ADV
fcis-30730	17	22	characterized	characterize	VERB
fcis-30730	17	23	as	as	ADP
fcis-30730	17	24	:	:	PUNCT
fcis-30730	17	25			NOUN
fcis-30730	17	26			SYM
fcis-30730	17	27	2	2	NUM
fcis-30730	17	28	1	1	NUM
fcis-30730	17	29	2	2	NUM
fcis-30730	17	30	2	2	NUM
fcis-30730	17	31	(	(	PUNCT
fcis-30730	17	32	(	(	PUNCT
fcis-30730	17	33	)	)	PUNCT
fcis-30730	17	34	)	)	PUNCT
fcis-30730	17	35	,	,	PUNCT
fcis-30730	17	36	exp	exp	NOUN
fcis-30730	17	37	(	(	PUNCT
fcis-30730	17	38	)	)	PUNCT
fcis-30730	18	1	ij	ij	INTJ
fcis-30730	19	1	ij	ij	INTJ
fcis-30730	19	2	f	f	NOUN
fcis-30730	20	1	i	i	INTJ
fcis-30730	20	2	c	c	NOUN
fcis-30730	21	1	f	f	NOUN
fcis-30730	22	1	i	i	PRON
fcis-30730	22	2	j	j	PROPN
fcis-30730	23	1	b	b	PROPN
fcis-30730	23	2			NOUN
fcis-30730	23	3			PROPN
fcis-30730	23	4			PROPN
fcis-30730	23	5			PROPN
fcis-30730	24	1			NOUN
fcis-30730	24	2			PROPN
fcis-30730	25	1			ADJ
fcis-30730	25	2			NOUN
fcis-30730	25	3	(	(	PUNCT
fcis-30730	25	4	2	2	NUM
fcis-30730	25	5	)	)	PUNCT
fcis-30730	25	6	the	the	DET
fcis-30730	25	7	fuzzy	fuzzy	ADJ
fcis-30730	25	8	inference	inference	NOUN
fcis-30730	25	9	layer	layer	NOUN
fcis-30730	25	10	is	be	AUX
fcis-30730	25	11	used	use	VERB
fcis-30730	25	12	as	as	ADP
fcis-30730	25	13	the	the	DET
fcis-30730	25	14	third	third	ADJ
fcis-30730	25	15	layer	layer	NOUN
fcis-30730	25	16	,	,	PUNCT
fcis-30730	25	17	whose	whose	DET
fcis-30730	25	18	neuron	neuron	NOUN
fcis-30730	25	19	nodes	node	NOUN
fcis-30730	25	20	correspond	correspond	VERB
fcis-30730	25	21	to	to	ADP
fcis-30730	25	22	the	the	DET
fcis-30730	25	23	fuzzy	fuzzy	ADJ
fcis-30730	25	24	rules	rule	NOUN
fcis-30730	25	25	one	one	NUM
fcis-30730	25	26	by	by	ADP
fcis-30730	25	27	one	one	NUM
fcis-30730	25	28	,	,	PUNCT
fcis-30730	25	29	and	and	CCONJ
fcis-30730	25	30	the	the	DET
fcis-30730	25	31	product	product	NOUN
fcis-30730	25	32	operation	operation	NOUN
fcis-30730	25	33	is	be	AUX
fcis-30730	25	34	used	use	VERB
fcis-30730	25	35	to	to	PART
fcis-30730	25	36	simulate	simulate	VERB
fcis-30730	25	37	the	the	DET
fcis-30730	25	38	logical	logical	ADJ
fcis-30730	25	39	computation	computation	NOUN
fcis-30730	25	40	of	of	ADP
fcis-30730	25	41	the	the	DET
fcis-30730	25	42	fuzzy	fuzzy	ADJ
fcis-30730	25	43	rules	rule	NOUN
fcis-30730	25	44	.	.	PUNCT
fcis-30730	26	1	there	there	PRON
fcis-30730	26	2	are	be	VERB
fcis-30730	26	3	49	49	NUM
fcis-30730	26	4	neuron	neuron	NOUN
fcis-30730	26	5	nodes	node	NOUN
fcis-30730	26	6	in	in	ADP
fcis-30730	26	7	the	the	DET
fcis-30730	26	8	third	third	ADJ
fcis-30730	26	9	layer	layer	NOUN
fcis-30730	26	10	,	,	PUNCT
fcis-30730	26	11	i.e.	i.e.	X
fcis-30730	26	12	,	,	PUNCT
fcis-30730	26	13	mn=49	mn=49	PROPN
fcis-30730	26	14	.	.	PUNCT
fcis-30730	27	1	the	the	DET
fcis-30730	27	2	input	input	NOUN
fcis-30730	27	3	and	and	CCONJ
fcis-30730	27	4	output	output	NOUN
fcis-30730	27	5	relation	relation	NOUN
fcis-30730	27	6	equation	equation	NOUN
fcis-30730	27	7	are	be	AUX
fcis-30730	27	8	:	:	PUNCT
fcis-30730	27	9			NOUN
fcis-30730	27	10			SYM
fcis-30730	27	11			NOUN
fcis-30730	27	12			SYM
fcis-30730	27	13			NOUN
fcis-30730	27	14	3	3	ADJ
fcis-30730	27	15	2	2	NUM
fcis-30730	27	16	21	21	NUM
fcis-30730	27	17	21	21	NUM
fcis-30730	27	18	,	,	PUNCT
fcis-30730	27	19	1,n	1,n	PROPN
fcis-30730	28	1	i	i	PRON
fcis-30730	28	2	f	f	X
fcis-30730	29	1	if	if	SCONJ
fcis-30730	29	2	f	f	PROPN
fcis-30730	29	3			X
fcis-30730	29	4	(	(	PUNCT
fcis-30730	29	5	3	3	NUM
fcis-30730	29	6	)	)	PUNCT
fcis-30730	29	7	the	the	DET
fcis-30730	29	8	fourth	fourth	ADJ
fcis-30730	29	9	layer	layer	NOUN
fcis-30730	29	10	is	be	AUX
fcis-30730	29	11	the	the	DET
fcis-30730	29	12	normalization	normalization	NOUN
fcis-30730	29	13	layer	layer	NOUN
fcis-30730	29	14	,	,	PUNCT
fcis-30730	29	15	which	which	PRON
fcis-30730	29	16	is	be	AUX
fcis-30730	29	17	responsible	responsible	ADJ
fcis-30730	29	18	for	for	ADP
fcis-30730	29	19	normalizing	normalize	VERB
fcis-30730	29	20	the	the	DET
fcis-30730	29	21	output	output	NOUN
fcis-30730	29	22	of	of	ADP
fcis-30730	29	23	the	the	DET
fcis-30730	29	24	fuzzy	fuzzy	ADJ
fcis-30730	29	25	inference	inference	NOUN
fcis-30730	29	26	layer	layer	NOUN
fcis-30730	29	27	,	,	PUNCT
fcis-30730	29	28	and	and	CCONJ
fcis-30730	29	29	its	its	PRON
fcis-30730	29	30	number	number	NOUN
fcis-30730	29	31	of	of	ADP
fcis-30730	29	32	neurons	neuron	NOUN
fcis-30730	29	33	remains	remain	VERB
fcis-30730	29	34	the	the	DET
fcis-30730	29	35	same	same	ADJ
fcis-30730	29	36	as	as	ADP
fcis-30730	29	37	that	that	PRON
fcis-30730	29	38	of	of	ADP
fcis-30730	29	39	the	the	DET
fcis-30730	29	40	third	third	ADJ
fcis-30730	29	41	layer	layer	NOUN
fcis-30730	29	42	(	(	PUNCT
fcis-30730	29	43	49	49	NUM
fcis-30730	29	44	nodes	node	NOUN
fcis-30730	29	45	)	)	PUNCT
fcis-30730	29	46	.	.	PUNCT
fcis-30730	30	1	the	the	DET
fcis-30730	30	2	input	input	NOUN
fcis-30730	30	3	-	-	PUNCT
fcis-30730	30	4	output	output	NOUN
fcis-30730	30	5	relationship	relationship	NOUN
fcis-30730	30	6	of	of	ADP
fcis-30730	30	7	this	this	DET
fcis-30730	30	8	layer	layer	NOUN
fcis-30730	30	9	is	be	AUX
fcis-30730	30	10	:	:	PUNCT
fcis-30730	30	11			NOUN
fcis-30730	30	12			SYM
fcis-30730	30	13			NOUN
fcis-30730	30	14			SYM
fcis-30730	30	15			NOUN
fcis-30730	30	16	4	4	NOUN
fcis-30730	30	17	3	3	NUM
fcis-30730	30	18	49	49	NUM
fcis-30730	30	19	3	3	NUM
fcis-30730	30	20	1	1	NUM
fcis-30730	30	21	/	/	SYM
fcis-30730	30	22	p	p	X
fcis-30730	31	1	f	f	X
fcis-30730	31	2	f	f	PROPN
fcis-30730	31	3	fl	fl	INTJ
fcis-30730	31	4	n	n	PROPN
fcis-30730	31	5	p	p	NOUN
fcis-30730	31	6			ADJ
fcis-30730	31	7			ADJ
fcis-30730	31	8			X
fcis-30730	31	9	(	(	PUNCT
fcis-30730	31	10	4	4	X
fcis-30730	31	11	)	)	PUNCT
fcis-30730	31	12	the	the	DET
fcis-30730	31	13	output	output	NOUN
fcis-30730	31	14	layer	layer	NOUN
fcis-30730	31	15	,	,	PUNCT
fcis-30730	31	16	as	as	ADP
fcis-30730	31	17	the	the	DET
fcis-30730	31	18	last	last	ADJ
fcis-30730	31	19	layer	layer	NOUN
fcis-30730	31	20	of	of	ADP
fcis-30730	31	21	the	the	DET
fcis-30730	31	22	network	network	NOUN
fcis-30730	31	23	,	,	PUNCT
fcis-30730	31	24	performs	perform	VERB
fcis-30730	31	25	defuzzification	defuzzification	NOUN
fcis-30730	31	26	operations	operation	NOUN
fcis-30730	31	27	on	on	ADP
fcis-30730	31	28	the	the	DET
fcis-30730	31	29	normalized	normalize	VERB
fcis-30730	31	30	data	datum	NOUN
fcis-30730	31	31	and	and	CCONJ
fcis-30730	31	32	outputs	output	NOUN
fcis-30730	31	33	the	the	DET
fcis-30730	31	34	modified	modify	VERB
fcis-30730	31	35	values	value	NOUN
fcis-30730	31	36	of	of	ADP
fcis-30730	31	37	the	the	DET
fcis-30730	31	38	pid	pid	NOUN
fcis-30730	31	39	control	control	NOUN
fcis-30730	31	40	parameters	parameter	NOUN
fcis-30730	31	41	.	.	PUNCT
fcis-30730	32	1	this	this	DET
fcis-30730	32	2	layer	layer	NOUN
fcis-30730	32	3	contains	contain	VERB
fcis-30730	32	4	a	a	DET
fcis-30730	32	5	total	total	NOUN
fcis-30730	32	6	of	of	ADP
fcis-30730	32	7	3	3	NUM
fcis-30730	32	8	neuron	neuron	NOUN
fcis-30730	32	9	nodes	node	NOUN
fcis-30730	32	10	with	with	ADP
fcis-30730	32	11	the	the	DET
fcis-30730	32	12	input	input	NOUN
fcis-30730	32	13	-	-	PUNCT
fcis-30730	32	14	output	output	NOUN
fcis-30730	32	15	relationship	relationship	NOUN
fcis-30730	32	16	:	:	PUNCT
fcis-30730	32	17			NOUN
fcis-30730	32	18			SYM
fcis-30730	32	19			NOUN
fcis-30730	32	20			NOUN
fcis-30730	32	21	4	4	NUM
fcis-30730	32	22	4	4	NUM
fcis-30730	32	23	4	4	NUM
fcis-30730	32	24	4	4	NUM
fcis-30730	32	25	9	9	NUM
fcis-30730	32	26	1	1	NUM
fcis-30730	32	27	,	,	PUNCT
fcis-30730	32	28	j	j	PROPN
fcis-30730	32	29	f	f	PROPN
fcis-30730	32	30	f	f	PROPN
fcis-30730	32	31	wl	wl	PROPN
fcis-30730	32	32	f	f	PROPN
fcis-30730	32	33	ww	ww	PROPN
fcis-30730	32	34	j	j	PROPN
fcis-30730	33	1			NUM
fcis-30730	34	1			NUM
fcis-30730	35	1			ADJ
fcis-30730	35	2			NOUN
fcis-30730	35	3			NUM
fcis-30730	35	4	(	(	PUNCT
fcis-30730	35	5	5	5	NUM
fcis-30730	35	6	)	)	PUNCT
fcis-30730	35	7	7	7	NUM
fcis-30730	35	8	in	in	ADP
fcis-30730	35	9	eq	eq	ADP
fcis-30730	35	10	.	.	PUNCT
fcis-30730	36	1	(	(	PUNCT
fcis-30730	36	2	5	5	NUM
fcis-30730	36	3	)	)	PUNCT
fcis-30730	36	4	,	,	PUNCT
fcis-30730	36	5	w	w	PROPN
fcis-30730	36	6	is	be	AUX
fcis-30730	36	7	the	the	DET
fcis-30730	36	8	connection	connection	NOUN
fcis-30730	36	9	weights	weight	NOUN
fcis-30730	36	10	;	;	PUNCT
fcis-30730	36	11	r	r	NOUN
fcis-30730	36	12	=	=	SYM
fcis-30730	36	13	1	1	NUM
fcis-30730	36	14	,	,	PUNCT
fcis-30730	36	15	2	2	NUM
fcis-30730	36	16	,	,	PUNCT
fcis-30730	36	17	3	3	NUM
fcis-30730	36	18	;	;	PUNCT
fcis-30730	37	1	l	l	NOUN
fcis-30730	37	2	=	=	SYM
fcis-30730	37	3	1	1	NUM
fcis-30730	37	4	,	,	PUNCT
fcis-30730	37	5	2	2	NUM
fcis-30730	37	6	,	,	PUNCT
fcis-30730	37	7	...	...	PUNCT
fcis-30730	37	8	,	,	PUNCT
fcis-30730	37	9	49	49	NUM
fcis-30730	37	10	.	.	PUNCT
fcis-30730	38	1	therefore	therefore	ADV
fcis-30730	38	2	,	,	PUNCT
fcis-30730	38	3	the	the	DET
fcis-30730	38	4	final	final	ADJ
fcis-30730	38	5	output	output	NOUN
fcis-30730	38	6	of	of	ADP
fcis-30730	38	7	the	the	DET
fcis-30730	38	8	fuzzy	fuzzy	ADJ
fcis-30730	38	9	neural	neural	ADJ
fcis-30730	38	10	network	network	NOUN
fcis-30730	38	11	is	be	AUX
fcis-30730	38	12	the	the	DET
fcis-30730	38	13	corrected	correct	VERB
fcis-30730	38	14	values	value	NOUN
fcis-30730	38	15	of	of	ADP
fcis-30730	38	16	the	the	DET
fcis-30730	38	17	three	three	NUM
fcis-30730	38	18	parameters	parameter	NOUN
fcis-30730	38	19	of	of	ADP
fcis-30730	38	20	the	the	DET
fcis-30730	38	21	pid	pid	NOUN
fcis-30730	38	22	controller	controller	NOUN
fcis-30730	38	23	:	:	PUNCT
fcis-30730	38	24			NOUN
fcis-30730	38	25			PROPN
fcis-30730	38	26			NOUN
fcis-30730	38	27			PUNCT
fcis-30730	38	28			NOUN
fcis-30730	38	29			NOUN
fcis-30730	38	30	5	5	NUM
fcis-30730	38	31	5	5	NUM
fcis-30730	38	32	5	5	NUM
fcis-30730	38	33	1	1	NUM
fcis-30730	38	34	2	2	NUM
fcis-30730	38	35	3	3	NUM
fcis-30730	38	36	p	p	NOUN
fcis-30730	39	1	i	i	NOUN
fcis-30730	40	1	d	d	NOUN
fcis-30730	40	2	f	f	X
fcis-30730	41	1	k	k	PROPN
fcis-30730	41	2	f	f	PROPN
fcis-30730	42	1	k	k	PROPN
fcis-30730	42	2	f	f	PROPN
fcis-30730	42	3	k	k	PROPN
fcis-30730	43	1			NUM
fcis-30730	43	2			NOUN
fcis-30730	44	1			NUM
fcis-30730	44	2			NOUN
fcis-30730	45	1			NUM
fcis-30730	45	2			NOUN
fcis-30730	46	1			NUM
fcis-30730	46	2			NUM
fcis-30730	46	3			PROPN
fcis-30730	46	4			NOUN
fcis-30730	46	5	(	(	PUNCT
fcis-30730	46	6	6	6	NUM
fcis-30730	46	7	)	)	PUNCT
fcis-30730	46	8	secondly	secondly	ADV
fcis-30730	46	9	,	,	PUNCT
fcis-30730	46	10	the	the	DET
fcis-30730	46	11	output	output	NOUN
fcis-30730	46	12	of	of	ADP
fcis-30730	46	13	the	the	DET
fcis-30730	46	14	fuzzy	fuzzy	ADJ
fcis-30730	46	15	neural	neural	ADJ
fcis-30730	46	16	network	network	NOUN
fcis-30730	46	17	pid	pid	NOUN
fcis-30730	46	18	controller	controller	NOUN
fcis-30730	46	19	is	be	AUX
fcis-30730	46	20	determined	determine	VERB
fcis-30730	46	21	.	.	PUNCT
fcis-30730	47	1	the	the	DET
fcis-30730	47	2	corrected	correct	VERB
fcis-30730	47	3	values	value	NOUN
fcis-30730	47	4	of	of	ADP
fcis-30730	47	5	the	the	DET
fcis-30730	47	6	three	three	NUM
fcis-30730	47	7	parameters	parameter	NOUN
fcis-30730	47	8	of	of	ADP
fcis-30730	47	9	the	the	DET
fcis-30730	47	10	pid	pid	NOUN
fcis-30730	47	11	are	be	AUX
fcis-30730	47	12	used	use	VERB
fcis-30730	47	13	as	as	ADP
fcis-30730	47	14	the	the	DET
fcis-30730	47	15	final	final	ADJ
fcis-30730	47	16	output	output	NOUN
fcis-30730	47	17	of	of	ADP
fcis-30730	47	18	the	the	DET
fcis-30730	47	19	fuzzy	fuzzy	ADJ
fcis-30730	47	20	neural	neural	ADJ
fcis-30730	47	21	network	network	NOUN
fcis-30730	47	22	,	,	PUNCT
fcis-30730	47	23	which	which	PRON
fcis-30730	47	24	also	also	ADV
fcis-30730	47	25	needs	need	VERB
fcis-30730	47	26	to	to	PART
fcis-30730	47	27	be	be	AUX
fcis-30730	47	28	summed	sum	VERB
fcis-30730	47	29	up	up	ADP
fcis-30730	47	30	with	with	ADP
fcis-30730	47	31	the	the	DET
fcis-30730	47	32	preset	preset	ADJ
fcis-30730	47	33	initial	initial	ADJ
fcis-30730	47	34	values	value	NOUN
fcis-30730	47	35	to	to	PART
fcis-30730	47	36	obtain	obtain	VERB
fcis-30730	47	37	the	the	DET
fcis-30730	47	38	output	output	NOUN
fcis-30730	47	39	value	value	NOUN
fcis-30730	47	40	of	of	ADP
fcis-30730	47	41	the	the	DET
fcis-30730	47	42	controller	controller	NOUN
fcis-30730	47	43	:	:	PUNCT
fcis-30730	47	44	0	0	NUM
fcis-30730	47	45	0	0	NUM
fcis-30730	47	46	0	0	NUM
fcis-30730	48	1	p	p	NOUN
fcis-30730	48	2	p	p	X
fcis-30730	49	1	p	p	X
fcis-30730	49	2	i	i	PRON
fcis-30730	50	1	i	i	PRON
fcis-30730	50	2	i	i	VERB
fcis-30730	51	1	d	d	NOUN
fcis-30730	51	2	d	d	PROPN
fcis-30730	52	1	d	d	X
fcis-30730	52	2	k	k	PROPN
fcis-30730	53	1	k	k	PROPN
fcis-30730	53	2	k	k	PROPN
fcis-30730	54	1	k	k	PROPN
fcis-30730	54	2	k	k	PROPN
fcis-30730	54	3	k	k	PROPN
fcis-30730	54	4	k	k	PROPN
fcis-30730	54	5	k	k	PROPN
fcis-30730	54	6	k	k	X
fcis-30730	55	1			ADV
fcis-30730	55	2			NUM
fcis-30730	55	3			NUM
fcis-30730	55	4			NUM
fcis-30730	55	5			NOUN
fcis-30730	55	6			PUNCT
fcis-30730	55	7			PUNCT
fcis-30730	55	8			PROPN
fcis-30730	55	9			PUNCT
fcis-30730	55	10			NOUN
fcis-30730	55	11			X
fcis-30730	55	12			NOUN
fcis-30730	55	13			NOUN
fcis-30730	55	14	(	(	PUNCT
fcis-30730	55	15	7	7	NUM
fcis-30730	55	16	)	)	PUNCT
fcis-30730	55	17	the	the	DET
fcis-30730	55	18	pid	pid	NOUN
fcis-30730	55	19	controller	controller	NOUN
fcis-30730	55	20	used	use	VERB
fcis-30730	55	21	in	in	ADP
fcis-30730	55	22	this	this	DET
fcis-30730	55	23	system	system	NOUN
fcis-30730	55	24	is	be	AUX
fcis-30730	55	25	incremental	incremental	ADJ
fcis-30730	55	26	control	control	NOUN
fcis-30730	55	27	:	:	PUNCT
fcis-30730	55	28	(	(	PUNCT
fcis-30730	55	29	)	)	PUNCT
fcis-30730	55	30	[	[	PUNCT
fcis-30730	55	31	(	(	PUNCT
fcis-30730	55	32	)	)	PUNCT
fcis-30730	55	33	(	(	PUNCT
fcis-30730	55	34	1	1	NUM
fcis-30730	55	35	)	)	PUNCT
fcis-30730	55	36	]	]	PUNCT
fcis-30730	55	37	(	(	PUNCT
fcis-30730	55	38	)	)	PUNCT
fcis-30730	55	39	[	[	PUNCT
fcis-30730	55	40	(	(	PUNCT
fcis-30730	55	41	)	)	PUNCT
fcis-30730	55	42	2	2	NUM
fcis-30730	55	43	(	(	PUNCT
fcis-30730	55	44	1	1	NUM
fcis-30730	55	45	)	)	PUNCT
fcis-30730	55	46	(	(	PUNCT
fcis-30730	55	47	2)]p	2)]p	NUM
fcis-30730	55	48	i	i	PRON
fcis-30730	55	49	du	du	VERB
fcis-30730	55	50	k	k	PROPN
fcis-30730	55	51	k	k	PROPN
fcis-30730	55	52	e	e	PROPN
fcis-30730	55	53	k	k	PROPN
fcis-30730	55	54	e	e	PROPN
fcis-30730	55	55	k	k	PROPN
fcis-30730	55	56	k	k	PROPN
fcis-30730	55	57	e	e	PROPN
fcis-30730	55	58	k	k	PROPN
fcis-30730	55	59	k	k	PROPN
fcis-30730	55	60	e	e	PROPN
fcis-30730	55	61	k	k	PROPN
fcis-30730	55	62	e	e	PROPN
fcis-30730	55	63	k	k	PROPN
fcis-30730	55	64	e	e	PROPN
fcis-30730	55	65	k	k	PROPN
fcis-30730	55	66			PROPN
fcis-30730	55	67			PROPN
fcis-30730	55	68			PROPN
fcis-30730	55	69			ADV
fcis-30730	55	70			PUNCT
fcis-30730	55	71			PROPN
fcis-30730	55	72			PROPN
fcis-30730	55	73			ADV
fcis-30730	55	74			PROPN
fcis-30730	55	75	(	(	PUNCT
fcis-30730	55	76	8)	8)	NUM
fcis-30730	55	77	honorific	honorific	ADJ
fcis-30730	55	78	title	title	NOUN
fcis-30730	55	79	(	(	PUNCT
fcis-30730	55	80	1	1	NUM
fcis-30730	55	81	)	)	PUNCT
fcis-30730	55	82	(	(	PUNCT
fcis-30730	55	83	)	)	PUNCT
fcis-30730	55	84	(	(	PUNCT
fcis-30730	55	85	1	1	X
fcis-30730	55	86	)	)	PUNCT
fcis-30730	55	87	(	(	PUNCT
fcis-30730	55	88	2	2	NUM
fcis-30730	55	89	)	)	PUNCT
fcis-30730	55	90	(	(	PUNCT
fcis-30730	55	91	)	)	PUNCT
fcis-30730	55	92	(	(	PUNCT
fcis-30730	55	93	3	3	X
fcis-30730	55	94	)	)	PUNCT
fcis-30730	55	95	(	(	PUNCT
fcis-30730	55	96	)	)	PUNCT
fcis-30730	55	97	2	2	NUM
fcis-30730	55	98	(	(	PUNCT
fcis-30730	55	99	1	1	NUM
fcis-30730	55	100	)	)	PUNCT
fcis-30730	55	101	(	(	PUNCT
fcis-30730	55	102	2	2	X
fcis-30730	55	103	)	)	PUNCT
fcis-30730	55	104	xc	xc	NOUN
fcis-30730	55	105	e	e	PROPN
fcis-30730	55	106	k	k	PROPN
fcis-30730	55	107	e	e	PROPN
fcis-30730	55	108	k	k	PROPN
fcis-30730	55	109	xc	xc	PROPN
fcis-30730	55	110	e	e	PROPN
fcis-30730	55	111	k	k	PROPN
fcis-30730	55	112	xc	xc	PROPN
fcis-30730	55	113	e	e	PROPN
fcis-30730	55	114	k	k	PROPN
fcis-30730	55	115	e	e	PROPN
fcis-30730	55	116	k	k	PROPN
fcis-30730	55	117	e	e	PROPN
fcis-30730	55	118	k	k	PROPN
fcis-30730	55	119			PROPN
fcis-30730	55	120			PROPN
fcis-30730	55	121			PROPN
fcis-30730	55	122			CCONJ
fcis-30730	55	123			X
fcis-30730	55	124			ADP
fcis-30730	56	1			PROPN
fcis-30730	56	2			NUM
fcis-30730	56	3			PROPN
fcis-30730	56	4			PROPN
fcis-30730	56	5			NUM
fcis-30730	56	6			NUM
fcis-30730	56	7			PROPN
fcis-30730	56	8			ADV
fcis-30730	56	9	(	(	PUNCT
fcis-30730	56	10	9	9	NUM
fcis-30730	56	11	)	)	PUNCT
fcis-30730	56	12	then	then	ADV
fcis-30730	56	13	eq	eq	NOUN
fcis-30730	56	14	.	.	PUNCT
fcis-30730	57	1	(	(	PUNCT
fcis-30730	57	2	8)	8)	NUM
fcis-30730	57	3	can	can	AUX
fcis-30730	57	4	be	be	AUX
fcis-30730	57	5	converted	convert	VERB
fcis-30730	57	6	to	to	ADP
fcis-30730	57	7	:	:	PUNCT
fcis-30730	57	8	(	(	PUNCT
fcis-30730	57	9	)	)	PUNCT
fcis-30730	57	10	(	(	PUNCT
fcis-30730	57	11	1	1	X
fcis-30730	57	12	)	)	PUNCT
fcis-30730	57	13	(	(	PUNCT
fcis-30730	57	14	2	2	NUM
fcis-30730	57	15	)	)	PUNCT
fcis-30730	57	16	(	(	PUNCT
fcis-30730	57	17	3)p	3)p	NOUN
fcis-30730	57	18	i	i	PRON
fcis-30730	57	19	du	du	VERB
fcis-30730	58	1	k	k	PROPN
fcis-30730	58	2	k	k	PROPN
fcis-30730	58	3	xc	xc	PROPN
fcis-30730	59	1	k	k	PROPN
fcis-30730	59	2	xc	xc	PROPN
fcis-30730	60	1	k	k	PROPN
fcis-30730	60	2	xc	xc	PROPN
fcis-30730	61	1			PROPN
fcis-30730	61	2			ADV
fcis-30730	61	3			X
fcis-30730	61	4	(	(	PUNCT
fcis-30730	61	5	10	10	NUM
fcis-30730	61	6	)	)	PUNCT
fcis-30730	61	7	the	the	DET
fcis-30730	61	8	output	output	NOUN
fcis-30730	61	9	of	of	ADP
fcis-30730	61	10	the	the	DET
fcis-30730	61	11	fuzzy	fuzzy	ADJ
fcis-30730	61	12	neural	neural	ADJ
fcis-30730	61	13	network	network	NOUN
fcis-30730	61	14	pid	pid	NOUN
fcis-30730	61	15	controller	controller	NOUN
fcis-30730	61	16	is	be	AUX
fcis-30730	61	17	:	:	PUNCT
fcis-30730	61	18	(	(	PUNCT
fcis-30730	61	19	)	)	PUNCT
fcis-30730	61	20	(	(	PUNCT
fcis-30730	61	21	)	)	PUNCT
fcis-30730	61	22	(	(	PUNCT
fcis-30730	61	23	1)u	1)u	NUM
fcis-30730	61	24	k	k	NOUN
fcis-30730	61	25	u	u	X
fcis-30730	61	26	k	k	PROPN
fcis-30730	61	27	u	u	NOUN
fcis-30730	61	28	k	k	PROPN
fcis-30730	61	29			PROPN
fcis-30730	61	30			NOUN
fcis-30730	61	31			PRON
fcis-30730	61	32			PUNCT
fcis-30730	61	33			X
fcis-30730	61	34	(	(	PUNCT
fcis-30730	61	35	11	11	NUM
fcis-30730	61	36	)	)	SYM
fcis-30730	61	37	3	3	NUM
fcis-30730	61	38	.	.	X
fcis-30730	61	39	simulation	simulation	NOUN
fcis-30730	61	40	and	and	CCONJ
fcis-30730	61	41	analysis	analysis	NOUN
fcis-30730	61	42	of	of	ADP
fcis-30730	61	43	fuzzy	fuzzy	ADJ
fcis-30730	61	44	neural	neural	ADJ
fcis-30730	61	45	pid	pid	NOUN
fcis-30730	61	46	controller	controller	NOUN
fcis-30730	61	47	in	in	ADP
fcis-30730	61	48	order	order	NOUN
fcis-30730	61	49	to	to	PART
fcis-30730	61	50	verify	verify	VERB
fcis-30730	61	51	the	the	DET
fcis-30730	61	52	advantages	advantage	NOUN
fcis-30730	61	53	of	of	ADP
fcis-30730	61	54	the	the	DET
fcis-30730	61	55	designed	design	VERB
fcis-30730	61	56	fuzzy	fuzzy	ADJ
fcis-30730	61	57	neural	neural	ADJ
fcis-30730	61	58	pid	pid	NOUN
fcis-30730	61	59	control	control	NOUN
fcis-30730	61	60	method	method	NOUN
fcis-30730	61	61	in	in	ADP
fcis-30730	61	62	heading	head	VERB
fcis-30730	61	63	control	control	NOUN
fcis-30730	61	64	,	,	PUNCT
fcis-30730	61	65	a	a	DET
fcis-30730	61	66	heading	head	VERB
fcis-30730	61	67	control	control	NOUN
fcis-30730	61	68	simulation	simulation	NOUN
fcis-30730	61	69	model	model	NOUN
fcis-30730	61	70	is	be	AUX
fcis-30730	61	71	established	establish	VERB
fcis-30730	61	72	based	base	VERB
fcis-30730	61	73	on	on	ADP
fcis-30730	61	74	matlab	matlab	PROPN
fcis-30730	61	75	/	/	SYM
fcis-30730	61	76	simulink	simulink	PROPN
fcis-30730	61	77	software	software	NOUN
fcis-30730	61	78	as	as	SCONJ
fcis-30730	61	79	shown	show	VERB
fcis-30730	61	80	in	in	ADP
fcis-30730	61	81	fig	fig	NOUN
fcis-30730	61	82	.	.	PUNCT
fcis-30730	62	1	2	2	NUM
fcis-30730	62	2	,	,	PUNCT
fcis-30730	62	3	which	which	PRON
fcis-30730	62	4	is	be	AUX
fcis-30730	62	5	used	use	VERB
fcis-30730	62	6	to	to	PART
fcis-30730	62	7	verify	verify	VERB
fcis-30730	62	8	the	the	DET
fcis-30730	62	9	method	method	NOUN
fcis-30730	62	10	and	and	CCONJ
fcis-30730	62	11	design	design	VERB
fcis-30730	62	12	the	the	DET
fcis-30730	62	13	heading	heading	ADJ
fcis-30730	62	14	tracking	tracking	NOUN
fcis-30730	62	15	test	test	NOUN
fcis-30730	62	16	with	with	ADP
fcis-30730	62	17	and	and	CCONJ
fcis-30730	62	18	without	without	ADP
fcis-30730	62	19	interference	interference	NOUN
fcis-30730	62	20	.	.	PUNCT
fcis-30730	63	1	fig	fig	NOUN
fcis-30730	63	2	2	2	NUM
fcis-30730	63	3	.	.	PUNCT
fcis-30730	64	1	heading	head	VERB
fcis-30730	64	2	maintenance	maintenance	NOUN
fcis-30730	64	3	simulation	simulation	NOUN
fcis-30730	64	4	model	model	NOUN
fcis-30730	64	5	in	in	ADP
fcis-30730	64	6	order	order	NOUN
fcis-30730	64	7	to	to	PART
fcis-30730	64	8	verify	verify	VERB
fcis-30730	64	9	the	the	DET
fcis-30730	64	10	performance	performance	NOUN
fcis-30730	64	11	advantages	advantage	NOUN
fcis-30730	64	12	of	of	ADP
fcis-30730	64	13	the	the	DET
fcis-30730	64	14	fuzzy	fuzzy	ADJ
fcis-30730	64	15	neural	neural	ADJ
fcis-30730	64	16	pid	pid	NOUN
fcis-30730	64	17	heading	head	VERB
fcis-30730	64	18	controller	controller	NOUN
fcis-30730	64	19	proposed	propose	VERB
fcis-30730	64	20	in	in	ADP
fcis-30730	64	21	this	this	DET
fcis-30730	64	22	paper	paper	NOUN
fcis-30730	64	23	,	,	PUNCT
fcis-30730	64	24	three	three	NUM
fcis-30730	64	25	groups	group	NOUN
fcis-30730	64	26	of	of	ADP
fcis-30730	64	27	controllers	controller	NOUN
fcis-30730	64	28	(	(	PUNCT
fcis-30730	64	29	traditional	traditional	ADJ
fcis-30730	64	30	pid	pid	NOUN
fcis-30730	64	31	,	,	PUNCT
fcis-30730	64	32	fuzzy	fuzzy	ADJ
fcis-30730	64	33	pid	pid	NOUN
fcis-30730	64	34	and	and	CCONJ
fcis-30730	64	35	fuzzy	fuzzy	ADJ
fcis-30730	64	36	neural	neural	ADJ
fcis-30730	64	37	pid	pid	NOUN
fcis-30730	64	38	)	)	PUNCT
fcis-30730	64	39	are	be	AUX
fcis-30730	64	40	compared	compare	VERB
fcis-30730	64	41	under	under	ADP
fcis-30730	64	42	the	the	DET
fcis-30730	64	43	same	same	ADJ
fcis-30730	64	44	test	test	NOUN
fcis-30730	64	45	conditions	condition	NOUN
fcis-30730	64	46	[	[	X
fcis-30730	64	47	5,6,7	5,6,7	NOUN
fcis-30730	64	48	]	]	PUNCT
fcis-30730	64	49	.	.	PUNCT
fcis-30730	65	1	by	by	ADP
fcis-30730	65	2	setting	set	VERB
fcis-30730	65	3	two	two	NUM
fcis-30730	65	4	typical	typical	ADJ
fcis-30730	65	5	tracking	tracking	NOUN
fcis-30730	65	6	heading	head	VERB
fcis-30730	65	7	angles	angle	NOUN
fcis-30730	65	8	of	of	ADP
fcis-30730	65	9	20	20	NUM
fcis-30730	65	10	°	°	NUM
fcis-30730	65	11	and	and	CCONJ
fcis-30730	65	12	40	40	NUM
fcis-30730	65	13	°	°	NOUN
fcis-30730	65	14	,	,	PUNCT
fcis-30730	65	15	the	the	DET
fcis-30730	65	16	performance	performance	NOUN
fcis-30730	65	17	differences	difference	NOUN
fcis-30730	65	18	of	of	ADP
fcis-30730	65	19	each	each	DET
fcis-30730	65	20	controller	controller	NOUN
fcis-30730	65	21	in	in	ADP
fcis-30730	65	22	terms	term	NOUN
fcis-30730	65	23	of	of	ADP
fcis-30730	65	24	overshooting	overshooting	NOUN
fcis-30730	65	25	amount	amount	NOUN
fcis-30730	65	26	,	,	PUNCT
fcis-30730	65	27	steady	steady	ADJ
fcis-30730	65	28	state	state	NOUN
fcis-30730	65	29	error	error	NOUN
fcis-30730	65	30	and	and	CCONJ
fcis-30730	65	31	regulation	regulation	NOUN
fcis-30730	65	32	time	time	NOUN
fcis-30730	65	33	are	be	AUX
fcis-30730	65	34	systematically	systematically	ADV
fcis-30730	65	35	analyzed	analyze	VERB
fcis-30730	65	36	[	[	X
fcis-30730	65	37	8	8	NUM
fcis-30730	65	38	]	]	PUNCT
fcis-30730	65	39	.	.	PUNCT
fcis-30730	66	1	(	(	PUNCT
fcis-30730	66	2	a	a	X
fcis-30730	66	3	)	)	PUNCT
fcis-30730	66	4	and	and	CCONJ
fcis-30730	66	5	(	(	PUNCT
fcis-30730	66	6	b	b	NOUN
fcis-30730	66	7	)	)	PUNCT
fcis-30730	66	8	in	in	ADP
fcis-30730	66	9	fig	fig	NOUN
fcis-30730	66	10	.	.	PUNCT
fcis-30730	67	1	3	3	NUM
fcis-30730	67	2	present	present	VERB
fcis-30730	67	3	the	the	DET
fcis-30730	67	4	heading	head	VERB
fcis-30730	67	5	keeping	keep	VERB
fcis-30730	67	6	trend	trend	NOUN
fcis-30730	67	7	of	of	ADP
fcis-30730	67	8	each	each	DET
fcis-30730	67	9	control	control	NOUN
fcis-30730	67	10	method	method	NOUN
fcis-30730	67	11	for	for	ADP
fcis-30730	67	12	the	the	DET
fcis-30730	67	13	desired	desire	VERB
fcis-30730	67	14	heading	heading	NOUN
fcis-30730	67	15	(	(	PUNCT
fcis-30730	67	16	20	20	NUM
fcis-30730	67	17	°	°	NUM
fcis-30730	67	18	and	and	CCONJ
fcis-30730	67	19	40	40	NUM
fcis-30730	67	20	°	°	NUM
fcis-30730	67	21	)	)	PUNCT
fcis-30730	67	22	,	,	PUNCT
fcis-30730	67	23	respectively	respectively	ADV
fcis-30730	67	24	,	,	PUNCT
fcis-30730	67	25	and	and	CCONJ
fcis-30730	67	26	table	table	NOUN
fcis-30730	67	27	1	1	NUM
fcis-30730	67	28	presents	present	VERB
fcis-30730	67	29	the	the	DET
fcis-30730	67	30	performance	performance	NOUN
fcis-30730	67	31	indexes	index	NOUN
fcis-30730	67	32	of	of	ADP
fcis-30730	67	33	each	each	DET
fcis-30730	67	34	control	control	NOUN
fcis-30730	67	35	method	method	NOUN
fcis-30730	67	36	.	.	PUNCT
fcis-30730	68	1	from	from	ADP
fcis-30730	68	2	fig	fig	NOUN
fcis-30730	68	3	.	.	PUNCT
fcis-30730	68	4	3	3	NUM
fcis-30730	68	5	and	and	CCONJ
fcis-30730	68	6	table	table	NOUN
fcis-30730	68	7	1	1	NUM
fcis-30730	68	8	,	,	PUNCT
fcis-30730	68	9	it	it	PRON
fcis-30730	68	10	can	can	AUX
fcis-30730	68	11	be	be	AUX
fcis-30730	68	12	seen	see	VERB
fcis-30730	68	13	that	that	SCONJ
fcis-30730	68	14	the	the	DET
fcis-30730	68	15	three	three	NUM
fcis-30730	68	16	kinds	kind	NOUN
fcis-30730	68	17	of	of	ADP
fcis-30730	68	18	controllers	controller	NOUN
fcis-30730	68	19	present	present	VERB
fcis-30730	68	20	a	a	DET
fcis-30730	68	21	significant	significant	ADJ
fcis-30730	68	22	difference	difference	NOUN
fcis-30730	68	23	when	when	SCONJ
fcis-30730	68	24	the	the	DET
fcis-30730	68	25	external	external	ADJ
fcis-30730	68	26	interference	interference	NOUN
fcis-30730	68	27	is	be	AUX
fcis-30730	68	28	not	not	PART
fcis-30730	68	29	taken	take	VERB
fcis-30730	68	30	into	into	ADP
fcis-30730	68	31	account	account	NOUN
fcis-30730	68	32	and	and	CCONJ
fcis-30730	68	33	the	the	DET
fcis-30730	68	34	given	give	VERB
fcis-30730	68	35	heading	heading	NOUN
fcis-30730	68	36	is	be	AUX
fcis-30730	68	37	20	20	NUM
fcis-30730	68	38	°	°	NUM
fcis-30730	68	39	and	and	CCONJ
fcis-30730	68	40	40	40	NUM
fcis-30730	68	41	°	°	NOUN
fcis-30730	68	42	.	.	PUNCT
fcis-30730	69	1	the	the	DET
fcis-30730	69	2	traditional	traditional	ADJ
fcis-30730	69	3	pid	pid	NOUN
fcis-30730	69	4	controller	controller	NOUN
fcis-30730	69	5	has	have	VERB
fcis-30730	69	6	the	the	DET
fcis-30730	69	7	largest	large	ADJ
fcis-30730	69	8	overshoot	overshoot	NOUN
fcis-30730	69	9	and	and	CCONJ
fcis-30730	69	10	steady	steady	ADJ
fcis-30730	69	11	-	-	PUNCT
fcis-30730	69	12	state	state	NOUN
fcis-30730	69	13	error	error	NOUN
fcis-30730	69	14	,	,	PUNCT
fcis-30730	69	15	the	the	DET
fcis-30730	69	16	longest	long	ADJ
fcis-30730	69	17	regulation	regulation	NOUN
fcis-30730	69	18	time	time	NOUN
fcis-30730	69	19	,	,	PUNCT
fcis-30730	69	20	and	and	CCONJ
fcis-30730	69	21	the	the	DET
fcis-30730	69	22	worst	bad	ADJ
fcis-30730	69	23	performance	performance	NOUN
fcis-30730	69	24	in	in	ADP
fcis-30730	69	25	each	each	DET
fcis-30730	69	26	index	index	NOUN
fcis-30730	69	27	;	;	PUNCT
fcis-30730	69	28	the	the	DET
fcis-30730	69	29	fuzzy	fuzzy	ADJ
fcis-30730	69	30	pid	pid	NOUN
fcis-30730	69	31	controller	controller	NOUN
fcis-30730	69	32	is	be	AUX
fcis-30730	69	33	optimized	optimize	VERB
fcis-30730	69	34	by	by	ADP
fcis-30730	69	35	the	the	DET
fcis-30730	69	36	fuzzy	fuzzy	ADJ
fcis-30730	69	37	rule	rule	NOUN
fcis-30730	69	38	controller	controller	NOUN
fcis-30730	69	39	parameters	parameter	NOUN
fcis-30730	69	40	,	,	PUNCT
fcis-30730	69	41	and	and	CCONJ
fcis-30730	69	42	there	there	PRON
fcis-30730	69	43	are	be	VERB
fcis-30730	69	44	limitations	limitation	NOUN
fcis-30730	69	45	in	in	ADP
fcis-30730	69	46	the	the	DET
fcis-30730	69	47	parameter	parameter	NOUN
fcis-30730	69	48	adaptivity	adaptivity	NOUN
fcis-30730	69	49	,	,	PUNCT
fcis-30730	69	50	although	although	SCONJ
fcis-30730	69	51	the	the	DET
fcis-30730	69	52	overshoot	overshoot	NOUN
fcis-30730	69	53	and	and	CCONJ
fcis-30730	69	54	the	the	DET
fcis-30730	69	55	regulation	regulation	NOUN
fcis-30730	69	56	time	time	NOUN
fcis-30730	69	57	have	have	AUX
fcis-30730	69	58	been	be	AUX
fcis-30730	69	59	improved	improve	VERB
fcis-30730	69	60	to	to	ADP
fcis-30730	69	61	a	a	DET
fcis-30730	69	62	certain	certain	ADJ
fcis-30730	69	63	extent	extent	NOUN
fcis-30730	69	64	compared	compare	VERB
fcis-30730	69	65	with	with	ADP
fcis-30730	69	66	that	that	PRON
fcis-30730	69	67	of	of	ADP
fcis-30730	69	68	the	the	DET
fcis-30730	69	69	traditional	traditional	ADJ
fcis-30730	69	70	pid	pid	NOUN
fcis-30730	69	71	controller	controller	NOUN
fcis-30730	69	72	,	,	PUNCT
fcis-30730	69	73	but	but	CCONJ
fcis-30730	69	74	the	the	DET
fcis-30730	69	75	performance	performance	NOUN
fcis-30730	69	76	of	of	ADP
fcis-30730	69	77	the	the	DET
fcis-30730	69	78	steady	steady	ADJ
fcis-30730	69	79	-	-	PUNCT
fcis-30730	69	80	state	state	NOUN
fcis-30730	69	81	error	error	NOUN
fcis-30730	69	82	control	control	NOUN
fcis-30730	69	83	is	be	AUX
fcis-30730	69	84	worse	bad	ADJ
fcis-30730	69	85	;	;	PUNCT
fcis-30730	69	86	by	by	ADP
fcis-30730	69	87	contrast	contrast	NOUN
fcis-30730	69	88	,	,	PUNCT
fcis-30730	69	89	the	the	DET
fcis-30730	69	90	fuzzy	fuzzy	ADJ
fcis-30730	69	91	neural	neural	ADJ
fcis-30730	69	92	pid	pid	NOUN
fcis-30730	69	93	controller	controller	NOUN
fcis-30730	69	94	relies	rely	VERB
fcis-30730	69	95	on	on	ADP
fcis-30730	69	96	the	the	DET
fcis-30730	69	97	neural	neural	ADJ
fcis-30730	69	98	network	network	NOUN
fcis-30730	69	99	-	-	PUNCT
fcis-30730	69	100	fuzzy	fuzzy	ADJ
fcis-30730	69	101	logic	logic	NOUN
fcis-30730	69	102	controller	controller	NOUN
fcis-30730	69	103	,	,	PUNCT
fcis-30730	69	104	and	and	CCONJ
fcis-30730	69	105	the	the	DET
fcis-30730	69	106	fuzzy	fuzzy	ADJ
fcis-30730	69	107	neural	neural	ADJ
fcis-30730	69	108	pid	pid	NOUN
fcis-30730	69	109	controller	controller	NOUN
fcis-30730	69	110	relies	rely	VERB
fcis-30730	69	111	on	on	ADP
fcis-30730	69	112	the	the	DET
fcis-30730	69	113	neural	neural	ADJ
fcis-30730	69	114	network	network	NOUN
fcis-30730	69	115	-	-	PUNCT
fcis-30730	69	116	fuzzy	fuzzy	ADJ
fcis-30730	69	117	logic	logic	NOUN
fcis-30730	69	118	controller	controller	NOUN
fcis-30730	69	119	.	.	PUNCT
fcis-30730	70	1	in	in	ADP
fcis-30730	70	2	contrast	contrast	NOUN
fcis-30730	70	3	,	,	PUNCT
fcis-30730	70	4	the	the	DET
fcis-30730	70	5	fuzzy	fuzzy	ADJ
fcis-30730	70	6	neural	neural	ADJ
fcis-30730	70	7	pid	pid	NOUN
fcis-30730	70	8	controller	controller	NOUN
fcis-30730	70	9	relies	rely	VERB
fcis-30730	70	10	on	on	ADP
fcis-30730	70	11	the	the	DET
fcis-30730	70	12	neural	neural	ADJ
fcis-30730	70	13	network	network	NOUN
fcis-30730	70	14	-	-	PUNCT
fcis-30730	70	15	fuzzy	fuzzy	ADJ
fcis-30730	70	16	logic	logic	NOUN
fcis-30730	70	17	synergistic	synergistic	ADJ
fcis-30730	70	18	optimization	optimization	NOUN
fcis-30730	70	19	mechanism	mechanism	NOUN
fcis-30730	70	20	to	to	PART
fcis-30730	70	21	achieve	achieve	VERB
fcis-30730	70	22	the	the	DET
fcis-30730	70	23	simultaneous	simultaneous	ADJ
fcis-30730	70	24	optimization	optimization	NOUN
fcis-30730	70	25	of	of	ADP
fcis-30730	70	26	the	the	DET
fcis-30730	70	27	overshooting	overshooting	NOUN
fcis-30730	70	28	amount	amount	NOUN
fcis-30730	70	29	(	(	PUNCT
fcis-30730	70	30	about	about	ADV
fcis-30730	70	31	6	6	NUM
fcis-30730	70	32	%	%	NOUN
fcis-30730	70	33	)	)	PUNCT
fcis-30730	70	34	,	,	PUNCT
fcis-30730	70	35	the	the	DET
fcis-30730	70	36	steady	steady	ADJ
fcis-30730	70	37	state	state	NOUN
fcis-30730	70	38	error	error	NOUN
fcis-30730	70	39	(	(	PUNCT
fcis-30730	70	40	almost	almost	ADV
fcis-30730	70	41	0	0	NUM
fcis-30730	70	42	)	)	PUNCT
fcis-30730	70	43	and	and	CCONJ
fcis-30730	70	44	the	the	DET
fcis-30730	70	45	regulation	regulation	NOUN
fcis-30730	70	46	time	time	NOUN
fcis-30730	70	47	(	(	PUNCT
fcis-30730	70	48	about	about	ADP
fcis-30730	70	49	14s	14	NOUN
fcis-30730	70	50	)	)	PUNCT
fcis-30730	70	51	.	.	PUNCT
fcis-30730	71	1	8	8	NUM
fcis-30730	71	2	(	(	PUNCT
fcis-30730	71	3	a)20	a)20	PROPN
fcis-30730	71	4	°	°	PROPN
fcis-30730	71	5	(	(	PUNCT
fcis-30730	71	6	b)40	b)40	PROPN
fcis-30730	71	7	°	°	ADJ
fcis-30730	71	8	fig	fig	NOUN
fcis-30730	71	9	3	3	X
fcis-30730	71	10	.	.	PUNCT
fcis-30730	72	1	holding	hold	VERB
fcis-30730	72	2	of	of	ADP
fcis-30730	72	3	heading	head	VERB
fcis-30730	72	4	for	for	ADP
fcis-30730	72	5	each	each	DET
fcis-30730	72	6	control	control	NOUN
fcis-30730	72	7	method	method	NOUN
fcis-30730	72	8	for	for	ADP
fcis-30730	72	9	different	different	ADJ
fcis-30730	72	10	desired	desire	VERB
fcis-30730	72	11	headings	heading	NOUN
fcis-30730	72	12	table	table	NOUN
fcis-30730	72	13	1	1	NUM
fcis-30730	72	14	.	.	PUNCT
fcis-30730	72	15	comparison	comparison	NOUN
fcis-30730	72	16	of	of	ADP
fcis-30730	72	17	the	the	DET
fcis-30730	72	18	performance	performance	NOUN
fcis-30730	72	19	index	index	NOUN
fcis-30730	72	20	of	of	ADP
fcis-30730	72	21	each	each	DET
fcis-30730	72	22	control	control	NOUN
fcis-30730	72	23	method	method	NOUN
fcis-30730	72	24	overtone	overtone	ADJ
fcis-30730	72	25	statistics	statistic	NOUN
fcis-30730	72	26	adjustment	adjustment	NOUN
fcis-30730	72	27	time	time	NOUN
fcis-30730	72	28	20	20	NUM
fcis-30730	72	29	°	°	NUM
fcis-30730	72	30	pid	pid	NOUN
fcis-30730	72	31	43	43	NUM
fcis-30730	72	32	%	%	NOUN
fcis-30730	72	33	0.0864	0.0864	NUM
fcis-30730	72	34	40.5	40.5	NUM
fcis-30730	72	35	fuzzy	fuzzy	ADJ
fcis-30730	72	36	pid	pid	NOUN
fcis-30730	72	37	12	12	NUM
fcis-30730	72	38	%	%	NOUN
fcis-30730	72	39	0.0791	0.0791	NUM
fcis-30730	72	40	16.3	16.3	NUM
fcis-30730	72	41	fuzzy	fuzzy	ADJ
fcis-30730	72	42	neural	neural	ADJ
fcis-30730	72	43	pid	pid	NOUN
fcis-30730	72	44	6	6	NUM
fcis-30730	72	45	%	%	NOUN
fcis-30730	72	46	0.0024	0.0024	NUM
fcis-30730	72	47	13.28	13.28	NUM
fcis-30730	72	48	40	40	NUM
fcis-30730	72	49	°	°	NUM
fcis-30730	72	50	pid	pid	NOUN
fcis-30730	73	1	45	45	NUM
fcis-30730	73	2	%	%	NOUN
fcis-30730	73	3	0.1488	0.1488	NUM
fcis-30730	73	4	41.08	41.08	NUM
fcis-30730	73	5	fuzzy	fuzzy	ADJ
fcis-30730	73	6	pid	pid	NOUN
fcis-30730	73	7	12	12	NUM
fcis-30730	73	8	%	%	NOUN
fcis-30730	73	9	0.1357	0.1357	NUM
fcis-30730	73	10	16.5	16.5	NUM
fcis-30730	73	11	fuzzy	fuzzy	ADJ
fcis-30730	73	12	neural	neural	ADJ
fcis-30730	73	13	pid	pid	NOUN
fcis-30730	73	14	6	6	NUM
fcis-30730	73	15	%	%	NOUN
fcis-30730	73	16	0.0011	0.0011	NUM
fcis-30730	73	17	13.5	13.5	NUM
fcis-30730	73	18	4	4	NUM
fcis-30730	73	19	.	.	PUNCT
fcis-30730	73	20	summary	summary	NOUN
fcis-30730	73	21	in	in	ADP
fcis-30730	73	22	this	this	DET
fcis-30730	73	23	article	article	NOUN
fcis-30730	73	24	,	,	PUNCT
fcis-30730	73	25	a	a	DET
fcis-30730	73	26	comparative	comparative	ADJ
fcis-30730	73	27	study	study	NOUN
fcis-30730	73	28	of	of	ADP
fcis-30730	73	29	pid	pid	PROPN
fcis-30730	73	30	,	,	PUNCT
fcis-30730	73	31	fuzzy	fuzzy	ADJ
fcis-30730	73	32	pid	pid	NOUN
fcis-30730	73	33	and	and	CCONJ
fcis-30730	73	34	fuzzy	fuzzy	ADJ
fcis-30730	73	35	neural	neural	ADJ
fcis-30730	73	36	pid	pid	NOUN
fcis-30730	73	37	control	control	NOUN
fcis-30730	73	38	methods	method	NOUN
fcis-30730	73	39	is	be	AUX
fcis-30730	73	40	carried	carry	VERB
fcis-30730	73	41	out	out	ADP
fcis-30730	73	42	to	to	PART
fcis-30730	73	43	address	address	VERB
fcis-30730	73	44	the	the	DET
fcis-30730	73	45	problem	problem	NOUN
fcis-30730	73	46	of	of	ADP
fcis-30730	73	47	heading	head	VERB
fcis-30730	73	48	control	control	NOUN
fcis-30730	73	49	of	of	ADP
fcis-30730	73	50	a	a	DET
fcis-30730	73	51	kelp	kelp	NOUN
fcis-30730	73	52	harvesting	harvesting	NOUN
fcis-30730	73	53	vessel	vessel	NOUN
fcis-30730	73	54	.	.	PUNCT
fcis-30730	74	1	the	the	DET
fcis-30730	74	2	response	response	NOUN
fcis-30730	74	3	characteristics	characteristic	NOUN
fcis-30730	74	4	of	of	ADP
fcis-30730	74	5	the	the	DET
fcis-30730	74	6	various	various	ADJ
fcis-30730	74	7	controllers	controller	NOUN
fcis-30730	74	8	were	be	AUX
fcis-30730	74	9	analyzed	analyze	VERB
fcis-30730	74	10	by	by	ADP
fcis-30730	74	11	establishing	establish	VERB
fcis-30730	74	12	the	the	DET
fcis-30730	74	13	control	control	NOUN
fcis-30730	74	14	strategy	strategy	NOUN
fcis-30730	74	15	model	model	NOUN
fcis-30730	74	16	and	and	CCONJ
fcis-30730	74	17	heading	head	VERB
fcis-30730	74	18	response	response	NOUN
fcis-30730	74	19	model	model	NOUN
fcis-30730	74	20	.	.	PUNCT
fcis-30730	75	1	it	it	PRON
fcis-30730	75	2	is	be	AUX
fcis-30730	75	3	found	find	VERB
fcis-30730	75	4	that	that	SCONJ
fcis-30730	75	5	the	the	DET
fcis-30730	75	6	fuzzy	fuzzy	ADJ
fcis-30730	75	7	neural	neural	ADJ
fcis-30730	75	8	pid	pid	NOUN
fcis-30730	75	9	heading	head	VERB
fcis-30730	75	10	controller	controller	NOUN
fcis-30730	75	11	has	have	VERB
fcis-30730	75	12	small	small	ADJ
fcis-30730	75	13	overshoot	overshoot	NOUN
fcis-30730	75	14	(	(	PUNCT
fcis-30730	75	15	about	about	ADV
fcis-30730	75	16	6	6	NUM
fcis-30730	75	17	%	%	NOUN
fcis-30730	75	18	)	)	PUNCT
fcis-30730	75	19	,	,	PUNCT
fcis-30730	75	20	small	small	ADJ
fcis-30730	75	21	static	static	ADJ
fcis-30730	75	22	error	error	NOUN
fcis-30730	75	23	(	(	PUNCT
fcis-30730	75	24	almost	almost	ADV
fcis-30730	75	25	0	0	NUM
fcis-30730	75	26	)	)	PUNCT
fcis-30730	75	27	and	and	CCONJ
fcis-30730	75	28	fast	fast	ADJ
fcis-30730	75	29	response	response	NOUN
fcis-30730	75	30	(	(	PUNCT
fcis-30730	75	31	about	about	ADP
fcis-30730	75	32	14s	14	NOUN
fcis-30730	75	33	)	)	PUNCT
fcis-30730	75	34	,	,	PUNCT
fcis-30730	75	35	and	and	CCONJ
fcis-30730	75	36	this	this	DET
fcis-30730	75	37	study	study	NOUN
fcis-30730	75	38	lays	lay	VERB
fcis-30730	75	39	a	a	DET
fcis-30730	75	40	technical	technical	ADJ
fcis-30730	75	41	foundation	foundation	NOUN
fcis-30730	75	42	for	for	ADP
fcis-30730	75	43	the	the	DET
fcis-30730	75	44	application	application	NOUN
fcis-30730	75	45	of	of	ADP
fcis-30730	75	46	highprecision	highprecision	NOUN
fcis-30730	75	47	heading	head	VERB
fcis-30730	75	48	control	control	NOUN
fcis-30730	75	49	system	system	NOUN
fcis-30730	75	50	on	on	ADP
fcis-30730	75	51	real	real	ADJ
fcis-30730	75	52	ships	ship	NOUN
fcis-30730	75	53	.	.	PUNCT
fcis-30730	76	1	acknowledgments	acknowledgment	NOUN
fcis-30730	76	2	this	this	DET
fcis-30730	76	3	project	project	NOUN
fcis-30730	76	4	is	be	AUX
fcis-30730	76	5	supported	support	VERB
fcis-30730	76	6	by	by	ADP
fcis-30730	76	7	the	the	DET
fcis-30730	76	8	key	key	ADJ
fcis-30730	76	9	r	r	NOUN
fcis-30730	76	10	&	&	CCONJ
fcis-30730	76	11	d	d	PROPN
fcis-30730	76	12	plan	plan	NOUN
fcis-30730	76	13	of	of	ADP
fcis-30730	76	14	shandong	shandong	PROPN
fcis-30730	76	15	province	province	PROPN
fcis-30730	76	16	under	under	ADP
fcis-30730	76	17	contracts	contract	NOUN
fcis-30730	76	18	2022cxgc020410	2022cxgc020410	NUM
fcis-30730	76	19	.	.	PUNCT
fcis-30730	77	1	references	reference	NOUN
fcis-30730	77	2	[	[	X
fcis-30730	77	3	1	1	X
fcis-30730	77	4	]	]	X
fcis-30730	77	5	liu	liu	PROPN
fcis-30730	77	6	lu	lu	PROPN
fcis-30730	77	7	.	.	PUNCT
fcis-30730	77	8	path	path	PROPN
fcis-30730	77	9	tracking	tracking	NOUN
fcis-30730	77	10	and	and	CCONJ
fcis-30730	77	11	cooperative	cooperative	ADJ
fcis-30730	77	12	control	control	NOUN
fcis-30730	77	13	of	of	ADP
fcis-30730	77	14	underdriven	underdriven	PROPN
fcis-30730	77	15	unmanned	unmanned	ADJ
fcis-30730	77	16	vessels	vessel	NOUN
fcis-30730	78	1	[	[	X
fcis-30730	78	2	d	d	X
fcis-30730	78	3	]	]	X
fcis-30730	78	4	.	.	PUNCT
fcis-30730	79	1	dalian	dalian	ADJ
fcis-30730	79	2	maritime	maritime	PROPN
fcis-30730	79	3	university	university	NOUN
fcis-30730	79	4	,	,	PUNCT
fcis-30730	79	5	2018	2018	NUM
fcis-30730	79	6	.	.	PUNCT
fcis-30730	80	1	[	[	X
fcis-30730	80	2	2	2	NUM
fcis-30730	80	3	]	]	X
fcis-30730	80	4	sun	sun	NOUN
fcis-30730	80	5	hairong	hairong	PROPN
fcis-30730	80	6	.	.	PUNCT
fcis-30730	81	1	research	research	NOUN
fcis-30730	81	2	on	on	ADP
fcis-30730	81	3	fuzzy	fuzzy	ADJ
fcis-30730	81	4	neural	neural	ADJ
fcis-30730	81	5	network	network	NOUN
fcis-30730	81	6	and	and	CCONJ
fcis-30730	81	7	its	its	PRON
fcis-30730	81	8	application	application	NOUN
fcis-30730	81	9	[	[	X
fcis-30730	81	10	d	d	X
fcis-30730	81	11	]	]	X
fcis-30730	81	12	.	.	PUNCT
fcis-30730	82	1	north	north	PROPN
fcis-30730	82	2	china	china	PROPN
fcis-30730	82	3	electric	electric	PROPN
fcis-30730	82	4	power	power	PROPN
fcis-30730	82	5	university	university	PROPN
fcis-30730	82	6	(	(	PUNCT
fcis-30730	82	7	hebei	hebei	PROPN
fcis-30730	82	8	)	)	PUNCT
fcis-30730	82	9	,	,	PUNCT
fcis-30730	82	10	2006	2006	NUM
fcis-30730	82	11	.	.	PUNCT
fcis-30730	83	1	[	[	X
fcis-30730	83	2	3	3	X
fcis-30730	83	3	]	]	PUNCT
fcis-30730	83	4	zhihong	zhihong	PROPN
fcis-30730	83	5	xu	xu	PROPN
fcis-30730	83	6	,	,	PUNCT
fcis-30730	83	7	xu	xu	PROPN
fcis-30730	83	8	ma	ma	PROPN
fcis-30730	83	9	,	,	PUNCT
fcis-30730	83	10	pengcheng	pengcheng	PROPN
fcis-30730	83	11	liu	liu	PROPN
fcis-30730	83	12	et	et	PROPN
fcis-30730	83	13	al	al	PROPN
fcis-30730	83	14	.	.	PROPN
fcis-30730	83	15	research	research	NOUN
fcis-30730	83	16	on	on	ADP
fcis-30730	83	17	heating	heating	NOUN
fcis-30730	83	18	room	room	NOUN
fcis-30730	83	19	temperature	temperature	NOUN
fcis-30730	83	20	control	control	NOUN
fcis-30730	83	21	based	base	VERB
fcis-30730	83	22	on	on	ADP
fcis-30730	83	23	fuzzy	fuzzy	ADJ
fcis-30730	83	24	neural	neural	ADJ
fcis-30730	83	25	network	network	NOUN
fcis-30730	83	26	sliding	slide	VERB
fcis-30730	83	27	mode	mode	NOUN
fcis-30730	83	28	variable	variable	ADJ
fcis-30730	83	29	structure	structure	NOUN
fcis-30730	83	30	.	.	PUNCT
fcis-30730	84	1	journal	journal	PROPN
fcis-30730	84	2	of	of	ADP
fcis-30730	84	3	tianjin	tianjin	PROPN
fcis-30730	84	4	polytechnic	polytechnic	PROPN
fcis-30730	84	5	university	university	PROPN
fcis-30730	84	6	,	,	PUNCT
fcis-30730	84	7	1	1	NUM
fcis-30730	84	8	-	-	SYM
fcis-30730	84	9	7	7	NUM
fcis-30730	85	1	[	[	X
fcis-30730	85	2	2024	2024	NUM
fcis-30730	85	3	-	-	SYM
fcis-30730	85	4	05	05	NUM
fcis-30730	85	5	-	-	SYM
fcis-30730	85	6	17	17	NUM
fcis-30730	85	7	]	]	PUNCT
fcis-30730	85	8	.	.	PUNCT
fcis-30730	86	1	[	[	X
fcis-30730	86	2	4	4	NUM
fcis-30730	86	3	]	]	X
fcis-30730	86	4	g.z	g.z	PROPN
fcis-30730	86	5	.	.	PROPN
fcis-30730	86	6	bai	bai	PROPN
fcis-30730	86	7	,	,	PUNCT
fcis-30730	86	8	j.h	j.h	PROPN
fcis-30730	86	9	.	.	PROPN
fcis-30730	86	10	yu	yu	PROPN
fcis-30730	86	11	.	.	PUNCT
fcis-30730	86	12	self	self	NOUN
fcis-30730	86	13	-	-	PUNCT
fcis-30730	86	14	tuning	tuning	NOUN
fcis-30730	86	15	of	of	ADP
fcis-30730	86	16	pid	pid	NOUN
fcis-30730	86	17	parameters	parameter	NOUN
fcis-30730	86	18	based	base	VERB
fcis-30730	86	19	on	on	ADP
fcis-30730	86	20	improved	improve	VERB
fcis-30730	86	21	fuzzy	fuzzy	ADJ
fcis-30730	86	22	neural	neural	ADJ
fcis-30730	86	23	network[j	network[j	PROPN
fcis-30730	86	24	]	]	PUNCT
fcis-30730	86	25	.	.	PUNCT
fcis-30730	87	1	computer	computer	NOUN
fcis-30730	87	2	application	application	NOUN
fcis-30730	87	3	research	research	NOUN
fcis-30730	87	4	,	,	PUNCT
fcis-30730	87	5	2016	2016	NUM
fcis-30730	87	6	,	,	PUNCT
fcis-30730	87	7	(	(	PUNCT
fcis-30730	87	8	11	11	NUM
fcis-30730	87	9	):	):	PUNCT
fcis-30730	87	10	3358	3358	NUM
fcis-30730	87	11	-	-	SYM
fcis-30730	87	12	3363	3363	NUM
fcis-30730	87	13	.	.	PUNCT
fcis-30730	88	1	[	[	X
fcis-30730	88	2	5	5	NUM
fcis-30730	88	3	]	]	PUNCT
fcis-30730	88	4	li	li	PROPN
fcis-30730	88	5	zhuo	zhuo	PROPN
fcis-30730	88	6	,	,	PUNCT
fcis-30730	88	7	xiao	xiao	PROPN
fcis-30730	88	8	deyun	deyun	PROPN
fcis-30730	88	9	,	,	PUNCT
fcis-30730	88	10	he	he	PRON
fcis-30730	88	11	shizhong	shizhong	VERB
fcis-30730	88	12	et	et	PROPN
fcis-30730	88	13	al	al	PROPN
fcis-30730	88	14	.	.	PROPN
fcis-30730	88	15	fuzzy	fuzzy	ADJ
fcis-30730	88	16	adaptive	adaptive	ADJ
fcis-30730	88	17	pid	pid	NOUN
fcis-30730	88	18	control	control	NOUN
fcis-30730	88	19	method	method	NOUN
fcis-30730	88	20	based	base	VERB
fcis-30730	88	21	on	on	ADP
fcis-30730	88	22	neural	neural	ADJ
fcis-30730	88	23	network[j	network[j	PROPN
fcis-30730	88	24	]	]	PUNCT
fcis-30730	88	25	.	.	PUNCT
fcis-30730	89	1	control	control	NOUN
fcis-30730	89	2	and	and	CCONJ
fcis-30730	89	3	decision	decision	NOUN
fcis-30730	89	4	making	making	NOUN
fcis-30730	89	5	,	,	PUNCT
fcis-30730	89	6	1996	1996	NUM
fcis-30730	89	7	,	,	PUNCT
fcis-30730	89	8	(	(	PUNCT
fcis-30730	89	9	03	03	NUM
fcis-30730	89	10	):	):	PUNCT
fcis-30730	89	11	340	340	NUM
fcis-30730	89	12	-	-	SYM
fcis-30730	89	13	345	345	NUM
fcis-30730	89	14	.	.	PUNCT
fcis-30730	90	1	[	[	X
fcis-30730	90	2	6	6	NUM
fcis-30730	90	3	]	]	PUNCT
fcis-30730	90	4	an	an	DET
fcis-30730	90	5	jt	jt	PROPN
fcis-30730	90	6	.	.	PUNCT
fcis-30730	90	7	research	research	NOUN
fcis-30730	90	8	and	and	CCONJ
fcis-30730	90	9	design	design	NOUN
fcis-30730	90	10	of	of	ADP
fcis-30730	90	11	intelligent	intelligent	ADJ
fcis-30730	90	12	pid	pid	NOUN
fcis-30730	90	13	controller	controller	NOUN
fcis-30730	90	14	based	base	VERB
fcis-30730	90	15	on	on	ADP
fcis-30730	90	16	fuzzy	fuzzy	ADJ
fcis-30730	90	17	neural	neural	ADJ
fcis-30730	90	18	network[d	network[d	NOUN
fcis-30730	90	19	]	]	PUNCT
fcis-30730	90	20	.	.	PUNCT
fcis-30730	91	1	wuhan	wuhan	PROPN
fcis-30730	91	2	university	university	PROPN
fcis-30730	91	3	of	of	ADP
fcis-30730	91	4	technology	technology	NOUN
fcis-30730	91	5	,	,	PUNCT
fcis-30730	91	6	2010	2010	NUM
fcis-30730	91	7	.	.	PUNCT
fcis-30730	92	1	[	[	X
fcis-30730	92	2	7	7	X
fcis-30730	92	3	]	]	X
fcis-30730	92	4	wang	wang	PROPN
fcis-30730	92	5	yan	yan	PROPN
fcis-30730	92	6	,	,	PUNCT
fcis-30730	92	7	deng	deng	PROPN
fcis-30730	92	8	yong	yong	PROPN
fcis-30730	92	9	,	,	PUNCT
fcis-30730	92	10	wang	wang	PROPN
fcis-30730	92	11	chao	chao	PROPN
fcis-30730	92	12	et	et	PROPN
fcis-30730	92	13	al	al	PROPN
fcis-30730	92	14	.	.	PROPN
fcis-30730	93	1	design	design	NOUN
fcis-30730	93	2	of	of	ADP
fcis-30730	93	3	fuzzy	fuzzy	ADJ
fcis-30730	93	4	neural	neural	ADJ
fcis-30730	93	5	network	network	NOUN
fcis-30730	93	6	pid	pid	NOUN
fcis-30730	93	7	controller	controller	NOUN
fcis-30730	93	8	based	base	VERB
fcis-30730	93	9	on	on	ADP
fcis-30730	93	10	improved	improve	VERB
fcis-30730	93	11	particle	particle	NOUN
fcis-30730	93	12	swarm	swarm	NOUN
fcis-30730	93	13	algorithm[j	algorithm[j	PROPN
fcis-30730	93	14	]	]	PUNCT
fcis-30730	93	15	.	.	PUNCT
fcis-30730	94	1	control	control	PROPN
fcis-30730	94	2	engineering	engineering	PROPN
fcis-30730	94	3	,	,	PUNCT
fcis-30730	94	4	2012	2012	NUM
fcis-30730	94	5	,	,	PUNCT
fcis-30730	94	6	(	(	PUNCT
fcis-30730	94	7	05	05	NUM
fcis-30730	94	8	):	):	PUNCT
fcis-30730	94	9	761	761	NUM
fcis-30730	94	10	-	-	SYM
fcis-30730	94	11	764	764	NUM
fcis-30730	94	12	.	.	PUNCT
fcis-30730	95	1	[	[	X
fcis-30730	95	2	8	8	NUM
fcis-30730	95	3	]	]	X
fcis-30730	95	4	yan	yan	PROPN
fcis-30730	95	5	shutian	shutian	PROPN
fcis-30730	95	6	,	,	PUNCT
fcis-30730	95	7	liu	liu	PROPN
fcis-30730	95	8	pengjun	pengjun	PROPN
fcis-30730	95	9	,	,	PUNCT
fcis-30730	95	10	su	su	PROPN
fcis-30730	95	11	yurui	yurui	PROPN
fcis-30730	95	12	et	et	PROPN
fcis-30730	95	13	al	al	PROPN
fcis-30730	95	14	.	.	PUNCT
fcis-30730	96	1	an	an	DET
fcis-30730	96	2	intelligent	intelligent	ADJ
fcis-30730	96	3	pid	pid	NOUN
fcis-30730	96	4	controller	controller	NOUN
fcis-30730	96	5	based	base	VERB
fcis-30730	96	6	on	on	ADP
fcis-30730	96	7	fuzzy	fuzzy	ADJ
fcis-30730	96	8	neural	neural	ADJ
fcis-30730	96	9	network	network	NOUN
fcis-30730	96	10	and	and	CCONJ
fcis-30730	96	11	genetic	genetic	ADJ
fcis-30730	96	12	algorithm[j	algorithm[j	PROPN
fcis-30730	96	13	]	]	PUNCT
fcis-30730	96	14	.	.	PUNCT
fcis-30730	97	1	journal	journal	PROPN
fcis-30730	97	2	of	of	ADP
fcis-30730	97	3	lanzhou	lanzhou	PROPN
fcis-30730	97	4	university	university	PROPN
fcis-30730	97	5	of	of	ADP
fcis-30730	97	6	technology	technology	NOUN
fcis-30730	97	7	,	,	PUNCT
fcis-30730	97	8	2006	2006	NUM
fcis-30730	97	9	,	,	PUNCT
fcis-30730	97	10	(	(	PUNCT
fcis-30730	97	11	04	04	NUM
fcis-30730	97	12	):	):	PUNCT
fcis-30730	97	13	42	42	NUM
fcis-30730	97	14	-	-	SYM
fcis-30730	97	15	45	45	NUM
fcis-30730	97	16	.	.	PUNCT