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Adaptive iterative learning control for a class of non-linearly parameterised systems with input saturations

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  • Ruikun Zhang
  • Zhongsheng Hou
  • Honghai Ji
  • Chenkun Yin

Abstract

In this paper, an adaptive iterative learning control scheme is proposed for a class of non-linearly parameterised systems with unknown time-varying parameters and input saturations. By incorporating a saturation function, a new iterative learning control mechanism is presented which includes a feedback term and a parameter updating term. Through the use of parameter separation technique, the non-linear parameters are separated from the non-linear function and then a saturated difference updating law is designed in iteration domain by combining the unknown parametric term of the local Lipschitz continuous function and the unknown time-varying gain into an unknown time-varying function. The analysis of convergence is based on a time-weighted Lyapunov–Krasovskii-like composite energy function which consists of time-weighted input, state and parameter estimation information. The proposed learning control mechanism warrants a L2[0, T] convergence of the tracking error sequence along the iteration axis. Simulation results are provided to illustrate the effectiveness of the adaptive iterative learning control scheme.

Suggested Citation

  • Ruikun Zhang & Zhongsheng Hou & Honghai Ji & Chenkun Yin, 2016. "Adaptive iterative learning control for a class of non-linearly parameterised systems with input saturations," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(5), pages 1084-1094, April.
    • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:5:p:1084-1094
    DOI: 10.1080/00207721.2014.911422
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    Cited by:

    1. Farah Bouakrif & Ahmad Taher Azar & Christos K. Volos & Jesus M. Muñoz-Pacheco & Viet-Thanh Pham, 2019. "Iterative Learning and Fractional Order Control for Complex Systems," Complexity, Hindawi, vol. 2019, pages 1-3, May.
    2. Qing-Yuan Xu & Wan-Ying He & Chuang-Tao Zheng & Peng Xu & Yun-Shan Wei & Kai Wan, 2022. "Adaptive Fuzzy Iterative Learning Control for Systems with Saturated Inputs and Unknown Control Directions," Mathematics, MDPI, vol. 10(19), pages 1-17, September.
    3. Yang, Nana & Li, Junmin & Chen, Jiaxi, 2020. "Fully distributed hybrid adaptive learning consensus protocols for a class of non-linearly parameterized multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 375(C).

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