Adaptive Asymptotic Tracking With Global Performance for Nonlinear Systems With Unknown Control Directions

• 成果类型: Article
• 署名作者: Zhao, Kai; Song, Yongduan; Chen, C. L. Philip; Chen, Long
• 署名单位: Chongqing University; University of Macau
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3074899
• 发表日期: 2022
• 页码: 1566-1573
• 关键词: Nonlinear systems; Adaptive systems; Time-varying systems; uncertainty; transient analysis; control design; Backstepping; Adaptive control; Global stability; prescribed performance; uncertain nonlinear systems; unknown control direction

摘要

This article presents a global adaptive asymptotic tracking control method, capable of guaranteeing prescribed transient behavior for uncertain strict-feedback nonlinear systems with arbitrary relative degree and unknown control directions. Unlike most existing funnel controls that are built upon time-varying feedback gains, the proposed method is derived from a tracking error-dependent normalized function and a barrier function, together with a time-varying scaling transformation, leading to an improved prescribed performance control solution with the following features: 1) the developed control is embedded with normalized error based adaptive parameter tuning and is able to ensure asymptotic tracking; 2) given transient performance is guaranteed in that the tracking error preserves in the prescribed boundary for for all t >= 0; and 3) it is able to cope with nonlinear systems with arbitrary relative degree, mismatched uncertainties, and unknown control directions. Both theoretical analysis and numerical simulations verify the effectiveness and benefits of the proposed method.