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Decentralized finite-time connective tracking control with prescribed settling time for p-normal form stochastic large-scale systems

Author

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  • Yang, Yi
  • Li, Xiaohua
  • Liu, Xiaoping

Abstract

This paper aims to solve the decentralized finite-time connective tracking control problem for p-normal form stochastic large-scale systems with output interconnections existing in both the drift and diffusion terms. By means of the stochastic system theory and a prescribed finite-time performance function (PFTPF), a novel design scheme is presented for the decentralized finite-time connective tracking controllers with an arbitrarily prescribed settling time. The connective stability problem of stochastic large-scale systems is investigated for the first time. In addition, a new solution for the decentralized tracking control problem of stochastic large-scale systems is presented via a novel mathematical treatment algorithm. The proposed controllers can ensure that the tracking errors converge to a predetermined region within an arbitrarily prescribed settling time and the controlled system is connectively bounded stable in probability. Three simulation examples are presented to exhibit the performance and the superiority of the new control strategy.

Suggested Citation

  • Yang, Yi & Li, Xiaohua & Liu, Xiaoping, 2022. "Decentralized finite-time connective tracking control with prescribed settling time for p-normal form stochastic large-scale systems," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    • Handle: RePEc:eee:apmaco:v:412:y:2022:i:c:s0096300321006652
    DOI: 10.1016/j.amc.2021.126581
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    References listed on IDEAS

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    1. Wang, Jing & Liang, Kun & Huang, Xia & Wang, Zhen & Shen, Hao, 2018. "Dissipative fault-tolerant control for nonlinear singular perturbed systems with Markov jumping parameters based on slow state feedback," Applied Mathematics and Computation, Elsevier, vol. 328(C), pages 247-262.
    2. Liyao Hu & Xiaohua Li, 2019. "Decentralised adaptive neural connectively finite-time control for a class of p-normal form large-scale nonlinear systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(16), pages 3003-3021, December.
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