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Journal of Control Science and Engineering
Volume 2014, Article ID 351568, 5 pages
Research Article

Design of Iterative Learning Control Method with Global Convergence Property for Nonlinear Systems

1Institute of Advanced Control Technology, Dalian University of Technology, Dalian 116024, China
2School of Software Technology, Dalian University of Technology, Dalian 116600, China

Received 17 April 2014; Revised 16 July 2014; Accepted 15 September 2014; Published 2 October 2014

Academic Editor: Zengqiang Chen

Copyright © 2014 Guang-Wei Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.