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Affect of state feedback on tracking performance of two types of nonlinear ILC systems

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Listed:
  • Zhang, Yamiao
  • Liu, Jian
  • Zheng, Yuanshi
  • Ruan, Xiaoe

Abstract

This paper considers how state feedback shapes the tracking performance of continuously nonlinear and locally Lipschitz nonlinear ILC systems with measurement noises, respectively. Under spectral radius condition, we first show that the continuous nonlinearity can ensure the bounded tracking performance. Then, under local Lipschitz nonlinearity, we establish the relations between steady-state/transient tracking performance and state feedback as well as the standard deviations of measurement noises, which reveal how state feedback and the standard deviations shape steady-state/transient tracking performance, and how to utilize state feedback to enhance steady-state/transient tracking performance. Finally, we use a numerical example with local Lipschitz nonlinearity to show the theoretical findings.

Suggested Citation

  • Zhang, Yamiao & Liu, Jian & Zheng, Yuanshi & Ruan, Xiaoe, 2026. "Affect of state feedback on tracking performance of two types of nonlinear ILC systems," Chaos, Solitons & Fractals, Elsevier, vol. 202(P2).
    • Handle: RePEc:eee:chsofr:v:202:y:2026:i:p2:s0960077925016108
    DOI: 10.1016/j.chaos.2025.117597
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    References listed on IDEAS

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    1. Jian Liu & Xiaoe Ruan & Qiang Zhang, 2020. "A joint control protocol for a class of uncertain nonlinear systems with iteration-varying trial length," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(12), pages 2276-2292, September.
    2. 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.
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