Event-based adaptive asymptotic tracking control of nonlinear time-varying systems with prescribed performance

Abstract

This paper is concerned with the adaptive tracking control problem of nonlinear time-varying systems. Based on the backstepping technology, an event-based prescribed performance control scheme is developed. And the time-varying uncertainties of the system are handled by utilising bound estimation method. The proposed controller not only ensures the prescribed tracking performance, but also reduces the communication burden. By using Lyapunov stability analysis, it is proven that all of the closed-loop signals are bounded, and the tracking error can converge to zero. Simultaneously, Zeno behaviour is excluded. Finally, the simulation results are utilised to illustrate the effectiveness of the proposed adaptive control scheme.

Keywords:

• Nonlinear time-varying systems
• event-triggered control (ETC)
• adaptive asymptotic tracking control
• prescribed performance

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported in part by the Funds of National Science of China [grant number 61973146]; in part by the Distinguished Young Scientifific Research Talents Plan in Liaoning Province [grant number XLYC1907077]; and in part by the Taishan Scholar Project of Shandong Province of China [grant number tsqn201909097].

Notes on contributors

Sheng-Nan Shi

Sheng-Nan Shi received a B.S. degree in Mathematics and Applied Mathematics from Binzhou University, Binzhou, China, in 2020. She is currently pursuing a M.S. degree in system theory from the Qingdao University, Qingdao, China. Her current research interests include adaptive control and ETC.

Yuan-Xin Li

Yuan-Xin Li received a B.S. degree in Mathematics and Applied Mathematics from Qufu Normal University, China, in 2007, the M.S. degree in Computational Mathematics from the College of Mathematical Sciences, Dalian University of Technology, Dalian, China, in 2009, and the Ph.D. degree in Control Theory and Control Engineering from the College of Information Science and Engineering, Northeastern University, Shenyang, China, in 2017. He is currently a professor in the Department of Science, Liaoning University of Technology, Jinzhou, China. His research interests include adaptive fuzzy/neural control, fault-tolerant control, ETC and adaptive control of cyber-physical systems.