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Iterative learning control for a class of uncertain nonlinear systems with current state feedback

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  • Jian Liu
  • Yamiao Zhang
  • Xiaoe Ruan

Abstract

In this paper, the problem of iterative learning control is addressed for a class of uncertain nonlinear systems with unknown input–output coupling parameters. Firstly, we prove that the control system is realisable if and only if all the input–output coupling parameters are nonzero. Secondly, to surmount the obstacle arising from the unknown input–output coupling parameters, a learning based identification technique is developed for the unknown input–output coupling parameters. Thirdly, a control protocol composed of iterative learning control update law and current state feedback is proposed for the controlled system. The findings suggest that the state feedback part does not change the realizability of controlled system and can be used to improve the transient tracking performance. Especially under certain condition, it can guarantee the monotone convergence of ILC process. Finally, simulation examples are provided to illustrate the effectiveness of the proposed control protocol.

Suggested Citation

  • Jian Liu & Yamiao Zhang & Xiaoe Ruan, 2019. "Iterative learning control for a class of uncertain nonlinear systems with current state feedback," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(10), pages 1889-1901, July.
    • Handle: RePEc:taf:tsysxx:v:50:y:2019:i:10:p:1889-1901
    DOI: 10.1080/00207721.2019.1645235
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    Cited by:

    1. Zhou, Min & Wang, JinRong & Shen, Dong, 2023. "Iterative learning control for continuous-time multi-agent differential inclusion systems with full learnability," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Yan Geng & Shouqin Wang & Xiaoe Ruan, 2022. "The Convergence of Data-Driven Optimal Iterative Learning Control for Linear Multi-Phase Batch Processes," Mathematics, MDPI, vol. 10(13), pages 1-19, July.
    3. Luo, Hongwei & Wang, JinRong & Shen, Dong, 2023. "Learning ability analysis for linear discrete delay systems with iteration-varying trial length," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).

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