Adaptive fuzzy tracking control for switched stochastic nonlinear systems with input constraint

Abstract

This paper investigates the problem of adaptive fuzzy tracking control for a class of uncertain strict-feedback stochastic nonlinear systems with input constraint under arbitrary switchings. The input constraint is approximated by a smooth function, and fuzzy logic systems are employed to identify the unknown nonlinear functions. On the basis of the backstepping technique and the common Lyapunov function method, a new adaptive fuzzy tracking control scheme is proposed, which ensures semi-globally uniformly ultimately boundedness in probability of all signals in the closed-loop systems and enables the reference signal to be tracked with bounded error. Finally, a numerical example is given to show the effectiveness of the developed control scheme.