Noise-Tolerant ZNN-Based Data-Driven Iterative Learning Control for Discrete Nonaffine Nonlinear MIMO Repetitive Systems

作     者：Yunfeng Hu Chong Zhang Bo Wang Jing Zhao Xun Gong Jinwu Gao Hong Chen Yunfeng Hu;Chong Zhang;Bo Wang;Jing Zhao;Xun Gong;Jinwu Gao;Hong Chen

作者机构：State Key Laboratory of Automotive Simulation and ControlJilin UniversityJilin UniversityChangchun 130025China College of Communication EngineeringJilin UniversityJilin UniversityChangchun 130025China Department of Electromechanical EngineeringUniversity of MacaoMacao 999078China School of Artificial IntelligenceJilin UniversityChangchun 130012China IEEE College of Electronics and Information EngineeringTongji UniversityShanghai 200092China 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2024年第11卷第2期

页      面：344-361页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 0811[工学-控制科学与工程] 

基　　金：supported by the National Natural Science Foundation of China(U21A20166) in part by the Science and Technology Development Foundation of Jilin Province (20230508095RC) in part by the Development and Reform Commission Foundation of Jilin Province (2023C034-3) in part by the Exploration Foundation of State Key Laboratory of Automotive Simulation and Control。 

主　　题：Adaptive control control system synthesis data-driven iterative learning control neurocontroller nonlinear discrete time systems 

摘      要：Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.