Design of Iterative Learning Control Method with Global Convergence Property for Nonlinear Systems. (1st October 2014)

• Record Type: Journal Article
• Authors: Xu, Guang-Wei; Shao, Cheng; Han, Yu
• Other Names: Chen Zengqiang Academic Editor.
• Is Part Of: Journal of control science and engineering. Volume 2014(2014)
• Publication Date: 2014-10-01
• Subjects: Control theory -- Periodicals; 629.831205
• DOI: 10.1155/2014/351568
• Languages: English
• ISSNs: 1687-5249

Abstract

Abstract : We address an iterative learning control (ILC) method for overcoming initial value problem caused by local convergence methods. Introducing a feedback recursive form of tracking errors into iterative learning law, this algorithm can avoid a crude linear approximation to nonlinear plants to reach global convergence property. The algorithm's structure is entirely illustrated. Under assumptions, it is guaranteed that tracking errors of the closed-loop system converge to zero. Besides, we discuss the roles of parameters in iterative learning law for algorithm realization, and a nonlinear case study is presented to demonstrate the effectiveness and tracking performance of the proposed algorithm.