Robust Adaptive Iterative Learning Control for a Generic Class of Uncertain Non-Square MIMO Systems

• 成果类型: Article
• 署名作者: Li, Xuefang; Hou, Zhongsheng
• 署名单位: Sun Yat Sen University; Qingdao University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2023.3335243
• 发表日期: 2024
• 页码: 2721-2728
• 关键词: uncertainty; MIMO communication; CONVERGENCE; Iterative learning control; control systems; Task analysis; Nonlinear systems; Adaptive iterative learning control (AILC); composite energy function; mismatched uncertainties; nonparametric uncertainties; nonsquare systems

摘要

In this work, the adaptive iterative learning control (AILC) for a generic class of nonsquare nonlinear systems is investigated in presence of unknown control gain matrices and nonparametric iteration-varying uncertainties. Differently from the existing approaches, the present work develops a unified, structurally simple and user-friendly AILC method, which is effective to handle nonlinear systems with parametric or nonparametric uncertainties, square or nonsquare input matrices, known or unknown control directions. From the design point of view, the proposed approach extends the AILC approach to nonsquare systems with unknown control gain matrices, which contributes significantly not only to refine the theory of AILC, but also to widen its application scope. The convergence of the proposed control algorithms are analysed rigorously by using the composite energy function methodology, and their effectiveness have been verified through an illustrated example.