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

Yi Yang, Xiaohua Li and Xiaoping Liu

Applied Mathematics and Computation, 2022, vol. 412, issue C

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.

Keywords: p-normal form stochastic large-scale systems; Decentralized control; Finite-time control; Prescribed settling time; Connectively stable (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:412:y:2022:i:c:s0096300321006652

DOI: 10.1016/j.amc.2021.126581

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