Observer-Based Adaptive Fuzzy Tracking Control for Stochastic Nonlinear Multi-Agent Systems with Dead-Zone Input

Abstract

This paper studies observer-based adaptive fuzzy leader-following tracking control for high-order stochastic nonlinear multi-agent systems with unknown dead-zone input. First, in order to deal with unmeasurable state variables, a reduced-order observer is established for each follower, which could make the computational burden of the systems reduced. Second, the fuzzy logic systems are introduced to approximate the stochastic disturbances and the unknown functions. Then, an adaptive fuzzy tracking controller is designed for high-order multi-agent systems with unknown dead-zone input by using the backstepping approach. Furthermore, it can be proved that all the closed-loop signals are bounded in probability, and the consensus error of the stochastic multi-agent systems can converge to a small region of origin under the Lyapunov stability theory. Finally, a simulation example is given to show the effectiveness of the designed algorithm.