Event-Triggered Adaptive Bipartite Containment Control for Stochastic Multiagent Systems
研究了随机非线性多智能体系统的事件触发自适应二分包含控制问题，通过设计误差补偿器和模糊逻辑系统，使跟随者输出收敛到领导者及其对称者形成的凸包内，并避免Zeno行为。
In this article, the adaptive bipartite containment control problem is investigated for stochastic nonlinear multiagent systems (MASs) with an event-triggered mechanism. It is known that the dynamic surface control method suffers from the mismatch between the virtual controller and the filter output. To address this issue, a novel error compensator is designed. Meanwhile, motivated by their universal approximation capability, fuzzy-logic systems (FLSs) are employed to identify the plants’ unknown nonlinear characteristics. To reduce the communication overhead, a distributed event-triggered control scheme is designed based on an estimate of unknown gain sign’s reciprocal. Leveraging the stochastic Lyapunov stability theory and backstepping design technique, it is proved that 1) the output responses of followers converge to a convex hull formed by those of the leaders and their symmetric ones; 2) all signals in the closed-loop system are semiglobally uniformly ultimately bounded in probability (SGUUBP); and 3) there is no Zeno behavior. Finally, simulation results are presented to illustrate the effectiveness of the proposed method.