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ESN-Observer-Based Adaptive Stabilization Control for Delayed Nonlinear Systems with Unknown Control Gain

Author

Listed:
  • Shuxian Lun

    (School of Control Science and Engineering, Bohai University, Jinzhou 121013, China)

  • Zhaoyi Lv

    (School of Control Science and Engineering, Bohai University, Jinzhou 121013, China)

  • Xiaodong Lu

    (School of Control Science and Engineering, Bohai University, Jinzhou 121013, China)

  • Ming Li

    (School of Control Science and Engineering, Bohai University, Jinzhou 121013, China)

Abstract

This paper investigates the observer-based adaptive stabilization control problem for a class of time-delay nonlinear systems with unknown control gain using an echo state network (ESN). In order to handle unknown functions, a new recurrent neural network (RNN) approximation method called ESN is utilized. It improves accuracy, reduces computing cost, and is simple to train. To address the issue of unknown control gain, the Nussbaum function is used, and the Lyapunov–Krasovskii functionals are used to address the delay term. The backstepping strategy and command filtering methodology are then used to create an adaptive stabilization controller. All of the closed-loop system’s signals are predicted to be confined by the Lyapunov stability theory. Finally, a simulation example is used to demonstrate the effectiveness of the suggested control mechanism.

Suggested Citation

  • Shuxian Lun & Zhaoyi Lv & Xiaodong Lu & Ming Li, 2023. "ESN-Observer-Based Adaptive Stabilization Control for Delayed Nonlinear Systems with Unknown Control Gain," Mathematics, MDPI, vol. 11(13), pages 1-21, July.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:2965-:d:1185850
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    References listed on IDEAS

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    1. Qing-Yuan Xu & Xiao-Dong Li, 2018. "Adaptive fuzzy ILC of nonlinear discrete-time systems with unknown dead zones and control directions," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(9), pages 1878-1894, July.
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