A high performance tracker for the sampled-data system based on iterative learning control

Fu Ming Chen, Jason Sheng-Hon Tsai, Fu-Zen Shaw, Tzong Jiy Tsai, Ming Hong Lin, Jun Yen Lin

研究成果: Article同行評審

摘要

A high performance tracker for the unknown stochastic sampled-data system based on iterative learning control (ILC) to be tracked is proposed in this paper. The newly developed ILC algorithm and the high-gain property tracker are first combined to speed up the convergence rate. The Euler method based difference type (D-type) ILC algorithm is proposed to combine with the prediction-based digital redesign method to construct the high performance modified D-type ILC for the model-based sampled-data systems. Finally, some examples are given for illustrating the effectiveness of the newly proposed method.

原文English
頁(從 - 到)29-39
頁數11
期刊International Journal of Control Theory and Applications
5
發行號1
出版狀態Published - 2012 十二月 1

All Science Journal Classification (ASJC) codes

  • 電腦科學(全部)

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