Disturbance-observer-based adaptive fuzzy control for nonlinear state constrained systems with input saturation and input delay

Abstract

In this paper, the problem of disturbance-observer-based adaptive fuzzy control is studied for nonlinear systems with full state constraints, input constraints and unknown external disturbance. Compared with existing results, the unknown compound disturbance is estimated by nonlinear-disturbance-observer (NDO) and the input delay is effectively processed by Pade approximation. Different from the mean value theorem and Nussbaum function method, an auxiliary variable is introduced to obtain the actual control input, which reduces the conservativeness of controller design. In order to solve the difficulties caused by input saturation and state constraints, the auxiliary design functions and Barrier Lyapunov functions (BLFs) are employed, respectively. By utilizing adaptive backstepping technique and Lyapunov stability theorem, a NDO-based novel controller is developed. It is proved that all the signals of the closed-loop systems are semi-globally uniformly ultimately bounded (SGUUB). The disturbance estimation errors and the tracking errors converge on a small neighborhood of the origin and the full state constraints are not violated. Simulation results are provided to demonstrate the effectiveness of the proposed method.