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Adaptive State-Feedback Stabilization for Stochastic Nonlinear Systems with Time-Varying Powers and Unknown Covariance

Author

Listed:
  • Jiabao Gu

    (School of Mathematics and Statistics Science, Ludong University, Yantai 264025, China)

  • Hui Wang

    (School of Mathematics and Statistics Science, Ludong University, Yantai 264025, China)

  • Wuquan Li

    (School of Mathematics and Statistics Science, Ludong University, Yantai 264025, China)

  • Ben Niu

    (School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China)

Abstract

This paper investigates the adaptive state-feedback stabilization problem for stochastic nonlinear systems. Compared with the existing results, we consider more general and more practical systems, i.e., systems with time-varying powers and unknown covariance simultaneously. We propose a new adaptive state-feedback control method, which ensures that the closed-loop system is globally stable in probability and the states are regulated to the origin almost surely. Finally, the feasibility of the design method is verified by two examples.

Suggested Citation

  • Jiabao Gu & Hui Wang & Wuquan Li & Ben Niu, 2022. "Adaptive State-Feedback Stabilization for Stochastic Nonlinear Systems with Time-Varying Powers and Unknown Covariance," Mathematics, MDPI, vol. 10(16), pages 1-16, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:16:p:2873-:d:885970
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    References listed on IDEAS

    as
    1. Li, Huijuan & Li, Wuquan & Gu, Jianzhong, 2022. "Decentralized stabilization of large-scale stochastic nonlinear systems with time-varying powers," Applied Mathematics and Computation, Elsevier, vol. 418(C).
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    4. Liu, Ji-Zhen & Yan, Shu & Zeng, De-Liang & Hu, Yong & Lv, You, 2015. "A dynamic model used for controller design of a coal fired once-through boiler-turbine unit," Energy, Elsevier, vol. 93(P2), pages 2069-2078.
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