Noise tolerant iterative learning control for a class of continuous-time systems |
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Authors: | Toshiharu Sugie [Author Vitae] Fumitoshi Sakai [Author Vitae] |
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Affiliation: | a Department of Systems Science, Graduate School of Informatics, Kyoto University, Uji, Kyoto 611-0011, Japan b Department of Mechanical Engineering, Nara National College of Technology, Yamatokoriyama, Nara 639-1080, Japan |
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Abstract: | The paper proposes a noise tolerant iterative learning control (ILC) for a class of linear continuous-time systems, which achieves high-precision tracking for uncertain plants by iteration of trials in the presence of heavy measurement noise. The robustness against measurement noise is achieved through (i) projection of continuous-time I/O signals onto a finite-dimensional parameter space, (ii) using error data of all past iterations via an integral operation in the learning law and (iii) noise reduction by H2 optimization subject to a specified convergence speed of the ILC. |
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Keywords: | Iterative learning control Tracking control Basis functions Continuous-time system |
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