Fixed-time neural consensus control for nonlinear multiagent systems with state and input quantization

Wenjing Cheng, Huidong Cheng, Fang Wang and Xueyi Zhang

Chaos, Solitons & Fractals, 2025, vol. 194, issue C

Abstract: In this article, a fixed-time distributed tracking control problem for unknown nonlinear multi-agent systems (MASs) is investigated. Unlike the existing works on quantized control for MASs, the input signals and states of each agent are communicated via directed networks and quantized before communication. The incorporation of quantized states into the virtual controllers results in their discontinuity, thereby rendering traditional backstepping technique inapplicable. To address this problem, the following steps are proposed: firstly, auxiliary intermediate controllers are designed using unquantized states. Secondly, by replacing the unquantized states with quantized states in the auxiliary intermediate controllers, both the intermediate controllers and the actual controller are obtained. Thirdly, to compensate for the impact of quantization errors, Lemma 10 is introduced. Furthermore, a new distributed adaptive fixed-time consensus (FTC) control strategy is established and the fixed-time stability of system is analyzed.

Keywords: Multi-agent systems; State and input quantization; Consensus; Fixed-time control; Backstepping (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:194:y:2025:i:c:s0960077925001584

DOI: 10.1016/j.chaos.2025.116145

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