Adaptive multi-dimensional Taylor network tracking control for a class of switched nonlinear systems with input nonlinearity. (September 2020)

• Record Type: Journal Article
• Authors: Zhu, Shan-Liang; Duan, De-Yu; Chu, Lei; Wang, Ming-Xin; Han, Yu-Qun; Xiong, Peng-Cheng
• Is Part Of: Transactions of the Institute of Measurement and Control. Volume 42:Number 13(2020)
• Page Start: 2482
• Page End: 2491
• Publication Date: 2020-09
• Subjects: Multi-dimensional Taylor network -- tracking control -- switched nonlinear systems -- input nonlinearity; Automatic control -- Periodicals; Measuring instruments -- Periodicals; Commande automatique -- Périodiques; Mesure -- Instruments -- Périodiques; 681.2
• DOI: 10.1177/0142331220916601
• Languages: English
• ISSNs: 0142-3312

Abstract

In this paper, a multi-dimensional Taylor network (MTN)-based adaptive tracking control approach is proposed for a class of switched nonlinear systems with input nonlinearity. Firstly, the input nonlinearity is assumed to be bounded by a sector interval. Secondly, with the help of MTNs approximating the unknown nonlinear functions, a novel adaptive MTN control scheme has the advantages of low cost, simple structure and real time feature is developed via backstepping technique. It is shown that the tracking error finally converges to a small domain around the origin and all signals in the closed-loop system are bounded. Finally, two examples are given to demonstrate the effectiveness of the proposed control scheme.