Adaptive neural network asymptotical tracking control for an uncertain nonlinear system with input quantisation

Abstract

In this paper, the problem of adaptive neural network asymptotical tracking is investigated for a class of nonlinear system with unknown function, external disturbances and input quantisation. Based on neural network technique, an adaptive asymptotical tracking controller is provided for an uncertain nonlinear system via backstepping method. In order to reduce complexity of the control algorithm in the backstepping design process, a sliding mode differentiator is employed to estimate the virtual control law and only two parameters need to be estimated via adaptive control technique. The stability of the closed-loop system is analysed by using Lyapunov function method and zero-tracking error performance is obtained in the presence of unknown nonlinear function, external disturbances and input quantisation. Finally, an application example is employed to demonstrate the effectiveness of the proposed scheme.

Keywords:

• Neural network
• sliding mode differentiator
• asymptotical tracking
• input quantisation
• uncertain nonlinear system

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [numbers 61773236, 61773235], part by the Taishan Scholar Project of Shandong Province, part by Natural Science Foundation of Shandong Province [ZR2016FQ09] and the China Postdoctoral Science Foundation [2017M612236, 2017M611222].

Notes on contributors

Haibin Sun

Haibin Sun was born in 1982. He is an associate professor in the School of Engineering at Qufu Normal University. He received his Ph.D degree in control theory and application from Southeast University in 2013. His research interests mainly lie inswitched control, anti-disturbance control and its application.

Linlin Hou

Linlin Hou was born in 1982. She received his B.S., M.S., and Ph.D.degreesfrom Qufu Normal University, in 2006, 2009, and 2012, respectively. Since 2012, she has been with theSchool of Information Science and Engineering, Qufu Normal University, whereshe is currently an associate professor. Her main research interests include stability, control, and robustness analysis of switched system, Markovian jump system.

Guangdeng Zong

Guangdeng Zong received the Ph.D. degree in control theory and application from Southeast University, Nanjing, China, in 2005. He is currently a Full Professor with the School of Engineering, Qufu Normal University, Jining, China. His current research interests include time-delay systems, switched systems, antidisturbance control and robust control.