Fixed‐/Finite‐Time Bipartite Consensus of Multi‐Agent Systems With Disturbances via Event‐Triggered Control and Neural Networks

This paper addresses the fixed‐time and finite‐time bipartite consensus problem for multi‐agent systems with nonlinearities and external disturbances under event‐triggered control. The problem is investigated for both leader‐following and leaderless configurations, and a scheme that reconciles communication efficiency with control performance is developed for systems featuring cooperative and antagonistic interactions. Designed to update control signals only when needed, a distributed event‐triggered mechanism reduces communication overhead and control costs while accommodating field constraints. Neural networks are employed to approximate the nonlinear dynamics, relaxing the Lipschitz conditions conventionally assumed and consequently lowering conservatism. Suitable Lyapunov functions are then constructed, and sufficient conditions for bipartite consensus are derived via fixed‐time and finite‐time stability theory. Zeno behavior is also theoretically precluded, so that practical implementability is ensured. Finally, numerical simulations corroborate the derived theoretical results.