A Class of Adaptive Control for Stochastic Nonlinear Systems Based on Backstepping Technology

Abstract

This paper discusses an adaptive control scheme for the stochastic nonlinear strict-feedback system with unknown interference signals and unknown input dead zones. Solving adaptive control problems often requires accurate information about the system model. When the unknown interfering signal is added to the system model, the design of the controller becomes more difficult. This paper uses the backstepping method to solve this adaptive control problem. Firstly, the mean-value theorem is applied to transform the strict-feedback nonlinearity into the measurable function. Secondly, In the design process of the backstepping method, the disturbance of the unknown interference signal is effectively controlled by selecting the appropriate adaptive rate. Further, the complete design process of the adaptive controller and proof of convergence are given. Finally, simulation example verify the feasibility of proposed adaptive controller.