Adaptive prescribed performance control for switched nonlinear systems with input saturation

ABSTRACT

In this paper, an adaptive prescribed performance output-feedback control scheme is proposed for a class of switched nonlinear systems with input saturation. The MT-filters are employed to estimate the unmeasured states and the unknown functions are approximated by the radial basis function neural networks in controller design procedure. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error satisfies the prescribed performance. Finally, simulation results are given to illustrate the effectiveness of the proposed approach.

KEYWORDS:

• Switched systems
• adaptive control
• MT-filters
• input saturation
• prescribed performance control

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 61273120], [grant number 61673219]; Jiangsu Six Talents Peaks Project of Province [grant number XNYQC-CXTD-001]; Tianjin Major Projects of Science and Technology [grant number 15ZXZNGX00250].

Notes on contributors

Shi Li

Shi Li received the M.Eng. degree in Control Theory and Control Engineering from Yangzhou University, Yangzhou, China, in 2016. Now, He is a Ph.D. degree candidate in Control Theory and Control Engineering from Nanjing University of Science and Technology, Nanjing, China. His current research interests include adaptive control, sampled-data control, nonlinear system and switched systems.

Zhengrong Xiang

Zhengrong Xiang received his Ph.D. degree in Control Theory and Control Engineering at Nanjing University of Science and Technology, Nanjing, China, in 1998. Since 1998 he has been faculty member and he is currently full professor at Nanjing University of Science and Technology. He was appointed as Lecturer in 1998 and Associate Professor in 2001 at Nanjing University of Science and Technology. He is a member of the IEEE, member of the Chinese Association for Artificial Intelligence. His main research interests include switched systems, nonlinear control, robust control, and networked control systems.