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Mathematical Problems in Engineering
Volume 2012, Article ID 705474, 14 pages
Research Article

Iterative Learning Control for Remote Control Systems with Communication Delay and Data Dropout

1State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China
2Department of Electrical and Information Engineering, Shaoxing College of Arts and Sciences, Shaoxing 31200, China
3Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576

Received 21 October 2011; Accepted 10 January 2012

Academic Editor: Yun-Gang Liu

Copyright © 2012 Chunping Liu 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.


Iterative learning control (ILC) is applied to remote control systems in which communication channels from the plant to the controller are subject to random data dropout and communication delay. Through analysis, it is shown that ILC can achieve asymptotical convergence along the iteration axis, as far as the probabilities of the data dropout and communication delay are known a priori. Owing to the essence of feedforward-based control ILC can perform trajectory-tracking tasks while both the data-dropout and the one-step delay phenomena are taken into consideration. Theoretical analysis and simulations validate the effectiveness of the ILC algorithm for network-based control tasks.