Neural Network Filtering Control Design for Nontriangular Structure Switched Nonlinear Systems in Finite Time

doi:10.1109/TNNLS.2018.2876352

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	Neural Network Filtering Control Design for Nontriangular Structure Switched Nonlinear Systems in Finite Time
	Sui, Shuai 1,2; Chen, C. L. Philip 2,3,4; Tong, Shaocheng 1
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN	2162-237X
	2019-07-01
卷号	30 期号:7 页码:2153-2162
通讯作者	Chen, C. L. Philip(philip.chen@ieee.org)
摘要	This paper solves the finite-time switching control issue for the nonstrict-feedhack nonlinear switched systems. The controlled plants contain immeasurable states, arbitrarily switchings, and the unknown functions which are constructed with the whole states. Neural network is used to simulate the uncertain systems and a filter-based state observer is designed to estimate the immeasurable states in this paper, respectively. Based on the backstepping recursive technique and the common Lyapunov function method, a finite-time switching control method is presented. Due to the developed finite-time control strategy, the closed-loop signals can he ensured to be bounded under arbitrarily switchings, and the outputs of systems can quickly track the desired reference signals in finite time. The effectiveness of the proposed method is given through its application to a massspring-damper system.
关键词	Common Lyapunov function finite time non-triangular structure switched systems
DOI	10.1109/TNNLS.2018.2876352
关键词[WOS]	TRACKING CONTROL ; ADAPTIVE STABILIZATION ; DELAY SYSTEMS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61572540] ; National Natural Science Foundation of China[61603167] ; National Natural Science Foundation of China[61773188] ; National Natural Science Foundation of China[61751202] ; National Natural Science Foundation of China[61751205] ; Macao Science and Technology Development Fund[079/2017/A2] ; Macao Science and Technology Development Fund[024/2015/AMJ] ; Macao Science and Technology Development Fund[019/2015/A1] ; University of Macau ; National Natural Science Foundation of China[61572540] ; National Natural Science Foundation of China[61603167] ; National Natural Science Foundation of China[61773188] ; National Natural Science Foundation of China[61751202] ; National Natural Science Foundation of China[61751205] ; Macao Science and Technology Development Fund[079/2017/A2] ; Macao Science and Technology Development Fund[024/2015/AMJ] ; Macao Science and Technology Development Fund[019/2015/A1] ; University of Macau
项目资助者	National Natural Science Foundation of China ; Macao Science and Technology Development Fund ; University of Macau
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000472605500018
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：151[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/27852
专题	离退休人员
通讯作者	Chen, C. L. Philip
作者单位	1.Liaoning Univ Technol, Coll Sci, Jinzhou 121001, Peoples R China 2.Univ Macau, Dept Comp & Informat Sci, Macau 999078, Peoples R China 3.Dalian Maritime Univ, Dalian 116026, Peoples R China 4.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100080, Peoples R China
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Sui, Shuai,Chen, C. L. Philip,Tong, Shaocheng. Neural Network Filtering Control Design for Nontriangular Structure Switched Nonlinear Systems in Finite Time[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2019,30(7):2153-2162.
APA	Sui, Shuai,Chen, C. L. Philip,&Tong, Shaocheng.(2019).Neural Network Filtering Control Design for Nontriangular Structure Switched Nonlinear Systems in Finite Time.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,30(7),2153-2162.
MLA	Sui, Shuai,et al."Neural Network Filtering Control Design for Nontriangular Structure Switched Nonlinear Systems in Finite Time".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 30.7(2019):2153-2162.