Removing Feasibility Conditions on Adaptive Neural Tracking Control of Nonlinear Time-Delay Systems With Time-Varying Powers, Input, and Full-State Constraints

doi:10.1109/TCYB.2020.3003327

	Removing Feasibility Conditions on Adaptive Neural Tracking Control of Nonlinear Time-Delay Systems With Time-Varying Powers, Input, and Full-State Constraints
	Guo, Chao 1,2; Xie, Xue-Jun 2; Hou, Zeng-Guang3
发表期刊	IEEE TRANSACTIONS ON CYBERNETICS
ISSN	2168-2267
	2022-04-01
卷号	52 期号:4 页码:2553-2564
通讯作者	Xie, Xue-Jun(xuejunxie@126.com)
摘要	This article investigates the tracking control for input and full-state-constrained nonlinear time-delay systems with unknown time-varying powers, whose nonlinearities do not impose any growth assumption. By utilizing the auxiliary control signal and nonlinear state-dependent transformation (NSDT) to counteract the effect of input saturation and cope with full-state constraints, respectively, and then introducing lower and higher powers and Lyapunov-Krasovskii (L-K) functionals in control design together with the adaptive neural-networks (NNs) method, an adaptive neural tracking control design is provided without feasibility conditions. It is proved that NNs approximation is valid, all the closed-loop signals are semiglobally bounded, and input and full-state constraints are not violated.
关键词	Nonlinear systems Time-varying systems Control design Adaptive systems Delay effects Artificial neural networks Automation Feasibility conditions input and full-state constraints neural networks (NNs) nonlinear systems time-varying powers
DOI	10.1109/TCYB.2020.3003327
关键词[WOS]	OUTPUT-FEEDBACK STABILIZATION ; BARRIER LYAPUNOV FUNCTIONS ; GLOBAL STABILIZATION ; NETWORK CONTROL
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFC2001700] ; Taishan Scholar Project of Shandong Province of China[ts201712040] ; National Natural Science Foundation of China[61673242]
项目资助者	National Key Research and Development Program of China ; Taishan Scholar Project of Shandong Province of China ; National Natural Science Foundation of China
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000778931500051
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：19[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/173211/48247
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Xie, Xue-Jun
作者单位	1.Dezhou Univ, Sch Math & Big Data, Dezhou 253023, Peoples R China 2.Qufu Normal Univ, Inst Automat, Qufu 273165, Shandong, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Guo, Chao,Xie, Xue-Jun,Hou, Zeng-Guang. Removing Feasibility Conditions on Adaptive Neural Tracking Control of Nonlinear Time-Delay Systems With Time-Varying Powers, Input, and Full-State Constraints[J]. IEEE TRANSACTIONS ON CYBERNETICS,2022,52(4):2553-2564.
APA	Guo, Chao,Xie, Xue-Jun,&Hou, Zeng-Guang.(2022).Removing Feasibility Conditions on Adaptive Neural Tracking Control of Nonlinear Time-Delay Systems With Time-Varying Powers, Input, and Full-State Constraints.IEEE TRANSACTIONS ON CYBERNETICS,52(4),2553-2564.
MLA	Guo, Chao,et al."Removing Feasibility Conditions on Adaptive Neural Tracking Control of Nonlinear Time-Delay Systems With Time-Varying Powers, Input, and Full-State Constraints".IEEE TRANSACTIONS ON CYBERNETICS 52.4(2022):2553-2564.