Event-Triggered Fuzzy Bipartite Tracking Control for Network Systems Based on Distributed Reduced-Order Observers
Hongjing Liang, Xiyue Guo, Yingnan Pan, Tingwen Huang
Abstract
This article studies the distributed observer-based event-triggered bipartite tracking control problem for stochastic nonlinear multiagent systems with input saturation. First, different from conventional observers, we construct a novel distributed reduced-order observer to estimate unknown states for the stochastic nonlinear systems. Then, an event-triggered mechanism with relative threshold is introduced to reduce the burden of communication. In addition, the bipartite tracking controller is proposed for stochastic multiagent systems by using fuzzy logic systems and the backstepping approach. Meanwhile, it is proved that the designed method can guarantee that all the signals in the closed-loop systems are bounded in probability, and the distributed consensus tracking errors can converge to a small neighborhood of the origin via the Lyapunov stability theory. Finally, a simulation example is given to prove the effectiveness of the designed scheme.