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

Author

Listed:
  • Cheng, Wenjing
  • Cheng, Huidong
  • Wang, Fang
  • Zhang, Xueyi

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.

Suggested Citation

  • Cheng, Wenjing & Cheng, Huidong & Wang, Fang & Zhang, Xueyi, 2025. "Fixed-time neural consensus control for nonlinear multiagent systems with state and input quantization," Chaos, Solitons & Fractals, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:chsofr:v:194:y:2025:i:c:s0960077925001584
    DOI: 10.1016/j.chaos.2025.116145
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