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Feedback-Based Iterative Learning Control for MIMO LTI Systems  

Doh, Tae-Yong (Department of Control and Instrumentation Engineering, Hanbat National University)
Ryoo, Jung-Rae (Department of Control and Instrumentation Engineering, Seoul National University of Technology)
Publication Information
International Journal of Control, Automation, and Systems / v.6, no.2, 2008 , pp. 269-277 More about this Journal
Abstract
This paper proposes a necessary and sufficient condition of convergence in the $L_2$-norm sense for a feedback-based iterative learning control (ILC) system including a multi-input multi-output (MIMO) linear time-invariant (LTI) plant. It is shown that the convergence conditions for a nominal plant and an uncertain plant are equal to the nominal performance condition and the robust performance condition in the feedback control theory, respectively. Moreover, no additional effort is required to design an iterative learning controller because the performance weighting matrix is used as an iterative learning controller. By proving that the least upper bound of the $L_2$-norm of the remaining tracking error is less than that of the initial tracking error, this paper shows that the iterative learning controller combined with the feedback controller is more effective to reduce the tracking error than only the feedback controller. The validity of the proposed method is verified through computer simulations.
Keywords
Convergence; iterative learning control (ILC)$L_2$-norm; least upper bound; multi-input multi-output (MIMO) linear time-invariant (LTI) systems; nominal performance; robust performance; structured singular value;
Citations & Related Records

Times Cited By Web Of Science : 3  (Related Records In Web of Science)
Times Cited By SCOPUS : 2
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