Time-/Event-Triggered Adaptive Neural Asymptotic Tracking Control of Nonlinear Interconnected Systems With Unmodeled Dynamics and Prescribed Performance

doi:10.1109/TNNLS.2021.3129228

	Time-/Event-Triggered Adaptive Neural Asymptotic Tracking Control of Nonlinear Interconnected Systems With Unmodeled Dynamics and Prescribed Performance
	Cheng, Ting-Ting 1; Niu, Ben 1; Zhang, Jia-Ming 1; Wang, Ding2,3 ; Wang, Zhen-Hua 1
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN	2162-237X
	2021-12-06
页码	11
通讯作者	Niu, Ben(niubensdnu@163.com) ; Wang, Zhen-Hua(wzhua111@126.com)
摘要	This article proposes two adaptive asymptotic tracking control schemes for a class of interconnected systems with unmodeled dynamics and prescribed performance. By applying an inherent property of radial basis function (RBF) neural networks (NNs), the design difficulties aroused from the unknown interactions among subsystems and unmodeled dynamics are overcome. Then, in order to ensure that the tracking errors can be suppressed in the specified range, the constrained control problem is transformed into the stabilization problem by using an auxiliary function. Based on the adaptive backstepping method, a time-triggered controller is constructed. It is proven that under the framework of Barbalat's lemma, all the variables in the closed-loop system are bounded and the tracking errors are further ensured to converge to zero asymptotically. Furthermore, the event-triggered strategy with a variable threshold is adopted to make more precise control such that the better system performance can be obtained, which reduces the system communication burden under the condition of limited communication resources. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed control scheme.
关键词	Interconnected systems Artificial neural networks Closed loop systems Multi-agent systems Asymptotic stability Switches Stability criteria Asymptotic tracking control event-triggered control neural networks (NNs) nonlinear interconnected systems prescribed performance control (PPC) unmodeled dynamics
DOI	10.1109/TNNLS.2021.3129228
关键词[WOS]	OUTPUT-FEEDBACK CONTROL ; FAULT-TOLERANT CONTROL ; DESIGN
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61873151] ; National Natural Science Foundation of China[61803237] ; National Natural Science Foundation of China[62073201] ; Shandong Provincial Natural Science Foundation of China[ZR2019MF009] ; Taishan Scholar Project of Shandong Province of China[tsqn201909078] ; Major Scientific and Technological Innovation Project of Shandong Province, China[2019JAZZ020812] ; Major Program of Shandong Province Natural Science Foundation, China[ZR2018ZB0419]
项目资助者	National Natural Science Foundation of China ; Shandong Provincial Natural Science Foundation of China ; Taishan Scholar Project of Shandong Province of China ; Major Scientific and Technological Innovation Project of Shandong Province, China ; Major Program of Shandong Province Natural Science Foundation, China
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:000732080600001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：10[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/173211/46819
专题	复杂系统管理与控制国家重点实验室
通讯作者	Niu, Ben; Wang, Zhen-Hua
作者单位	1.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250014, Shandong, Peoples R China 2.Beijing Univ Technol, Fac Informat Technol, Beijing 100124, 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	Cheng, Ting-Ting,Niu, Ben,Zhang, Jia-Ming,et al. Time-/Event-Triggered Adaptive Neural Asymptotic Tracking Control of Nonlinear Interconnected Systems With Unmodeled Dynamics and Prescribed Performance[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2021:11.
APA	Cheng, Ting-Ting,Niu, Ben,Zhang, Jia-Ming,Wang, Ding,&Wang, Zhen-Hua.(2021).Time-/Event-Triggered Adaptive Neural Asymptotic Tracking Control of Nonlinear Interconnected Systems With Unmodeled Dynamics and Prescribed Performance.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,11.
MLA	Cheng, Ting-Ting,et al."Time-/Event-Triggered Adaptive Neural Asymptotic Tracking Control of Nonlinear Interconnected Systems With Unmodeled Dynamics and Prescribed Performance".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021):11.