Adaptive output feedback quantised tracking control for stochastic nonstrict-feedback nonlinear systems with input saturation

ABSTRACT

This paper is concerned with the problem of adaptive output feedback quantised tracking control for a class of stochastic nonstrict-feedback nonlinear systems with asymmetric input saturation. Especially, both input and output signals are quantised by two sector-bounded quantisers. In order to solve the technical difficulties originating from asymmetric saturation nonlinearities and sector-bounded quantisation errors, some special technique, approximation-based methods and Gaussian error function-based continuous differentiable model are exploited. Meanwhile, an observer including the quantised input and output signals is designed to estimate the states. Then, a novel output feedback adaptive quantised control scheme is proposed to ensure that all signals in the closed-loop system are 4-moment (2-moment) semi-globally uniformly ultimately bounded while the output signal follows a desired reference signal. Finally, the effectiveness and applicability of the design methodology is illustrated with two simulation examples.

KEYWORDS:

• Stochastic nonlinear systems
• adaptive control
• output feedback
• quantisation
• input saturation

Acknowledgments

The authors would like to appreciate the editors and reviewers for their valuable comments and kind help.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is partially supported by the Chinese National Natural Science Foundation [grant number 71871135], and Shanghai Pujiang Program [grant number 15PJC049], and Fundamental Research Funds for the Central Universities [grant numbers 222201714055 and 222201717006].

Notes on contributors

Yekai Yang

Yekai Yang received the B.S. degree in measurement and control technology and instrumentation from Wuhan Institute of Technology, Wuhan, China, in 2016. He is currently pursuing the M.S. degree in control theory and control engineering with the East China University of Science and Technology, Shanghai, China. His current research interests include nonlinear control, stochastic systems and quantized control.

Zhaoxu Yu

Zhaoxu Yu received the M.S. degree in Applied Mathematics from Tongji University, Shanghai, China, and the Ph.D. degree in Control Science and Engineering from Shanghai Jiaotong University, Shanghai, China, in 2001 and 2004, respectively. He is currently an associate professor with the Department of Automation in East China University of Science and Technology. From July 2014 to July 2015, he was a Visiting Scholar in the Department of Electrical and Computer Engineering, University of Florida, USA. His research interest includes nonlinear control, adaptive control and stochastic system.

Shugang Li

Shugang Li is an associate professor in the School of management at Shanghai University, Shanghai, China. He received his Ph.D. degree in control engineering from Shanghai Jiao Tong University in 2004. His current research areas of interest are information system and information management, data mining, soft computing and artificial intelligence.