Adaptive fuzzy dynamic surface tracking control for a class of nonlinear systems with unknown distributed time delays and backlash-like hysteresis. (3rd October 2017)

• Record Type: Journal Article
• Authors: Yue, Hongyun; Wei, Zongtian; Chen, Qingjiang; Zhang, Xiaoyan
• Is Part Of: International journal of advanced robotic systems. Volume 14:Number 5(2017:Sep./Oct.)
• Publication Date: 2017-10-03
• Subjects: Adaptive fuzzy backstepping control -- observer -- Lyapunov–Krasovskii functionals -- dynamic surface control -- time-varying delays -- backlash-like hysteresis; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881417733886
• Languages: English
• ISSNs: 1729-8806

Abstract

In this article, an adaptive fuzzy backstepping dynamic surface control approach is developed for a class of nonlinear systems with unknown backlash-like hysteresis and unknown state discrete and distributed time-varying delays. Fuzzy logic systems are used to approximate the unknown nonlinear functions and a fuzzy state observer is designed for estimating the immeasurable states. Then, by combining the backstepping technique and the appropriate Lyapunov–Krasovskii functionals with the dynamic surface control approach, the output-feedback adaptive fuzzy tracking controller is designed. The main advantages of this article are (i) the existence of the state discrete and distributed time-varying delays such that the investigated systems are more general than that of the existing results, (ii) the proposed control scheme can eliminate the problem of "explosion of complexity" inherent in the backstepping design method, and (iii) for the n th nonlinear system, only one fuzzy logic system is used to approximate the unknown continuous time-varying delay functions since all of them are lumped into one unknown nonlinear function, which makes our design scheme easier to be implemented in practical applications. It is proven that the proposed design method is able to guarantee that all the signals in the closed-loop system are bounded and the tracking error can converge to a small neighborhood of origin with an appropriate choice of design parameters. Finally, the simulation results demonstrate the effectiveness of the proposed approach.