Adaptive fuzzy asymptotical tracking control of nonlinear systems with unmodeled dynamics and quantized actuator

• Published in: Information sciences Vol. 575; pp. 779 - 792
• Main Authors: Wang, Huanqing, Xiaoping Liu, Peter, Xie, Xuejun, Liu, Xiaoping, Hayat, Tasawar, Alsaadi, Fuad E.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.10.2021
• Subjects: Adaptive fuzzy control; Input quantization; Non-strict-feedback systems; Unmodeled dynamics; Adaptive fuzzy control; Input quantization; Non-strict-feedback systems; Unmodeled dynamics
• ISSN: 0020-0255; 1872-6291
• DOI: 10.1016/j.ins.2018.04.011

This paper studies the problem of adaptive fuzzy asymptotical quantized tracking control of non-strict-feedback systems with unmodeled dynamics. A dynamic signal is used to cope with the unmodeled dynamics and fuzzy systems are introduced to approximate the packaged unknown nonlinearities. Based on backstepping technique and fuzzy approximation property, a systemic fuzzy adaptive control scheme is proposed. By the utilization of Lyapunov theory, the semi-globally uniformly ultimate boundedness of all closed-loop system signals and asymptotical tracking performance are guaranteed. The main contributions of this work are two aspects: (i) a backstepping-based quantized control algorithm is firstly extended to nonlinear systems with unmodeled dynamics and non-strict-feedback structure; (ii) the semi-globally asymptotic tracking control scheme is independent of the quantized parameter. Simulation results verify the presented control approach.