Approximation-based adaptive tracking control of stochastic nonlinear systems with a general form

In this paper, an approximation-based adaptive tracking control scheme is proposed for a class of stochastic nonlinear systems with a more general structure. Fuzzy logical systems are used to approximate unknown nonlinearities in the controller design procedure and the backstepping technique is utilized to construct a state-feedback adaptive controller. The proposed controller can guarantee that all the signals in the closed-loop system are fourth-moment semi-globally uniformly ultimately bounded and the tracking error eventually converges to a small neighborhood around the origin. Simulation results are used to show the effectiveness of the proposed control scheme.