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Adaptive Fixed-Time NN-Based Tracking Control for a Type of Stochastic Nonlinear Systems Subject to Input Saturation

Author

Listed:
  • Daohong Zhu

    (College of Mathematics and Computer Science, Tongling University, Tongling 244061, China)

  • Zhenzhen Long

    (School of Mathematics and Statistics, Anhui Normal University, Wuhu 241005, China)

  • Liandi Fang

    (College of Mathematics and Computer Science, Tongling University, Tongling 244061, China
    School of Mathematics and Statistics, Anhui Normal University, Wuhu 241005, China)

Abstract

This paper considers the adaptive fixed-time tracking control problem for stochastic systems subject to input saturation. Firstly, a smooth function approximation method is utilized to eliminate the effect of input saturation. Then, by combining the neural networks (NNs) approximation method with the backstepping-like technique, an adaptive fixed-time tracking control scheme is explicitly developed. The proposed scheme can ensure that the state variables are bounded in probability and the tracking error converges to a small region of the equilibrium point in a fixed time. Eventually, two numerical examples are given to indicate the performance and effectiveness of the presented strategy.

Suggested Citation

  • Daohong Zhu & Zhenzhen Long & Liandi Fang, 2025. "Adaptive Fixed-Time NN-Based Tracking Control for a Type of Stochastic Nonlinear Systems Subject to Input Saturation," Mathematics, MDPI, vol. 13(12), pages 1-20, June.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:12:p:2018-:d:1682202
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