Event-Triggered Sliding Mode Consensus of Heterogeneous Agent Networks: A Lie-Algebraic Decoupling Approach

This paper investigates the fuzzy event-triggered sliding mode consensus tracking problem for T-S heterogeneous agent networks by a Lie-algebra decoupling approach. To relax the restrictive assumption of identical input matrices in conventional fuzzy sliding mode control, we employ Lie algebra controllability conditions to decouple agent dynamics. Based on the decoupled dynamics, a sliding surface is designed to ensure rapid consensus convergence and robustness to uncertainties. Subsequently, a novel event-triggered mechanism is proposed by directly utilizing the sliding surface error. This design dynamically adjusts the triggering threshold, effectively reducing transmission resources without disrupting system stability. To mitigate performance degradation during event-triggered intervals, a hybrid controller is developed. It integrates adaptive nonlinear functions with boundary layer techniques, maintaining performance during non-triggering intervals. Furthermore, rigorous analysis based on Lyapunov theory effectively demonstrates the reachability of the sliding surface and the leader-following consensus of the T-S fuzzy multiagent systems. Concurrently, the exclusion of Zeno behavior is achieved by establishing theoretical constraints on the minimum time interval between successive events. Ultimately, simulation results demonstrate the scheme’s effectiveness.