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An adaptive discrete-time ILC strategy using fuzzy systems for iteration-varying reference trajectory tracking

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Abstract

In this article, a novel fuzzy systems based on adaptive Iterative Learning Control (ILC) strategy is presented to deal with a class of non-parametric nonlinear discrete-time systems which perform iteration-varying reference trajectory tracking. Using the technique of fuzzy systems to compensate for the non-parametric uncertainty of the discrete-time system dynamics, the proposed adaptive ILC scheme can well track the iteration-varying reference trajectory beyond the initial time points. The convergence of the fuzzy systems based adaptive ILC algorithm is guaranteed by theoretical analysis, and a numerical example is given to illustrate the effectiveness of the adaptive ILC scheme.

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Author information

Authors and Affiliations

  1. School of Information Science and Technology, Sun Yat-sen University, Key Lab of Machine Intelligence and Advanced Computing, Ministry of Education, Guangzhou, 510006, China

    Teng-Fei Xiao & Xiao-Dong Li

  2. Department of Mechanical and Biomedical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong

    John K. L. Ho

Authors
  1. Teng-Fei Xiao
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  2. Xiao-Dong Li
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  3. John K. L. Ho
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Corresponding author

Correspondence to Xiao-Dong Li.

Additional information

Teng-Fei Xiao received his B.S. and M.Phil. degrees from the School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China, in 2009 and 2012, respectively. His research interests include iterative learning control and control of distributed parameter system.

Xiao-Dong Li received his B.S. degree from the Department of Mathematics, Shaanxi Normal University, Xian, China, in 1987, the M.Phil. degree from the Nanjing University of Science and Technology, Nanjing, China, in 1990, and the Ph.D. degree from the City University of Hong Kong, Hong Kong, in 2007. He is currently a Professor in the School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China. His research interests include 2-D system theory, iterative learning control, and artificial intelligence.

John K. L. Ho received his BSc & MSc degrees in Computer, Control Engineering from the Coventry University and his Ph.D. degree from the University of East London, UK. He has many years design experience in the field of automation when was working in GEC Electrical Projects Ltd in UK. Currently, he is an Associate Professor in the Department of Mechanical and Biomedical Engineering, City University of Hong Kong. His research interests are in the fields of control engineering, enterprise automation and product design.

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Xiao, TF., Li, XD. & Ho, J.K.L. An adaptive discrete-time ILC strategy using fuzzy systems for iteration-varying reference trajectory tracking. Int. J. Control Autom. Syst. 13, 222–230 (2015). https://doi.org/10.1007/s12555-013-0474-1

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  • DOI: https://doi.org/10.1007/s12555-013-0474-1

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