Event-triggered output feedback containment control for a class of stochastic nonlinear multi-agent systems

Yang Yang, Xiaorui Xi, Songtao Miao and Jinran Wu

Applied Mathematics and Computation, 2022, vol. 418, issue C

Abstract: An output feedback-based containment control strategy is proposed with an event-triggered mechanism for a class of stochastic nonlinear multi-agent systems (MASs). For unavailable internal states of individual agent, a state observer is constructed for their estimations. The dynamic surface control (DSC) technology is employed to improve traditional backstepping, where a first-order filter is introduced for derivation calculation of virtual control laws. For the purpose of reducing communication resources, a fixed threshold-based triggered strategy is presented to reduce data transmission bits over communication channels. It is proven that all signals in the closed-loop system are bounded in probability and the containment control is achieved. Finally, the effectiveness of the proposed control strategy is verified via two examples.

Keywords: Containment; Dynamic surface; Event-triggered; Neural networks; Stochastic multi-agent systems (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:418:y:2022:i:c:s0096300321009000

DOI: 10.1016/j.amc.2021.126817

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