Dynamic surface control for a class of stochastic non‐linear systems with input saturation

Abstract

In this study, the problem of adaptive dynamic surface control (DSC) design is investigated for a class of stochastic non‐linear systems with input saturation. The saturation non‐linearity is modelled via the existing dead zone‐based model of saturation. Furthermore, the packaged unknown functions are tackled using the neural networks. On the basis of the DSC technique, an adaptive controller is designed for stochastic non‐linear systems with input saturation. The proposed control scheme can guarantee the closed‐loop system stability, which shows that all closed‐loop system signals are semi‐globally uniformly ultimately bounded in the sense of probability and the tracking error converges to a small neighbourhood of the origin. Simulation results are provided to demonstrate the effectiveness and performance of the proposed approach.