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This paper investigates distributed consensus control for nonlinear multi-agent systems (MASs) subject to random switching topologies and external disturbances. A novel control framework integrates Least Squares Support Vector Machine (LS-SVM)-based data-driven modeling, a dual hidden Markov model (DHMM), and a dynamic event-triggered mechanism. LS-SVM is used to approximate unknown agent dynamics offline, converting the original system into a unified affine form. The DHMM characterizes stochastic switching in both system parameters and communication topologies, improving adaptability to dynamic environments. A dynamic event-triggered strategy is designed to reduce communication load and prevent Zeno behavior. A Lyapunov–Krasovskii functional and Schur’s complement are employed to derive sufficient LMI conditions ensuring extended dissipativity and consensus under switching. Simulation results on a nonlinear MAS validate the proposed method’s effectiveness and robustness.

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Extended Dissipative Consensus Control for Nonlinear MASs Under Random Topologies Using LSSVM and Dual Hidden Markov Models

  • 会议论文

  • 发表日期：

    2026年

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  • Jinquan Chu,
  • Shutao Wang,
  • Yaomin Li,
  • Zihui Zhang,
  • Senping Jia

摘要

This paper investigates distributed consensus control for nonlinear multi-agent systems (MASs) subject to random switching topologies and external disturbances. A novel control framework integrates Least Squares Support Vector Machine (LS-SVM)-based data-driven modeling, a dual hidden Markov model (DHMM), and a dynamic event-triggered mechanism. LS-SVM is used to approximate unknown agent dynamics offline, converting the original system into a unified affine form. The DHMM characterizes stochastic switching in both system parameters and communication topologies, improving adaptability to dynamic environments. A dynamic event-triggered strategy is designed to reduce communication load and prevent Zeno behavior. A Lyapunov–Krasovskii functional and Schur’s complement are employed to derive sufficient LMI conditions ensuring extended dissipativity and consensus under switching. Simulation results on a nonlinear MAS validate the proposed method’s effectiveness and robustness.