Robust adaptive controller using universal approximators for nonlinear systems under input constraint

This paper describes a design of the robust adaptive controller for a nonlinear dynamical system with unknown nonlinearities. These unknown nonlinearities are approximated by a linearly-parameterized universal approximators (LPUA) whose parameters are adjusted on-line according to some adaptive laws for the purpose of controlling the output of the nonlinear system to track a given trajectory. The Lyapunov synthesis approach is used to develop a state-feedback adaptive control algorithm based on the adaptive LPUA model. The main contribution of this paper is to present a method to consider input constraint with rigorous stability proof. The overall control system guarantees that the tracking error converges in the small neighborhood of zero, and that all signals involved are uniformly bounded. Theoretical results are illustrated through a simulation example.