Prescribed Performance Adaptive Fuzzy Control of Stochastic Nonlinear Multi-agent Systems with Input Hysteresis and Saturation

This paper studies the adaptive fuzzy control issue for a category of stochastic nonlinear multi-agent systems with input hysteresis and saturations in non-affine form. Fuzzy logic systems are employed to approximate the unknown nonlinear functions. By introducing a Nussbaum function, the unknown gain problem caused by input hysteresis and saturation hybrid term can be solved effectively. Based on the backstepping scheme, dynamic surface control approach, and by introducing performance function, an adaptive fuzzy consensus controller is constructed to guarantee that the synchronize error converges to a prescribed performance. Based on the Lyapunov stability theory, it is testified that all the closed-loop system variables are uniformly ultimately bounded in probability; meanwhile, the followers’ outputs ultimately synchronize for the leader with bounded tracking errors. Finally, two examples are presented to verify the availability of the presented method.