Nonlinear receding horizon control: Stable output feedback and adaptive techniques.

摘要

Over the past ten years, many researchers contributed to the development of stable state feedback nonlinear receding horizon controller design techniques. However, the output feedback and adaptive problems have not been well-addressed in the literature.; In this work, a sampled-data output feedback receding horizon control technique for a class of nonlinear systems is presented. The controller combines a globally stabilizing state feedback receding horizon control with a discretized high gain observer to achieve semi-global practical stability of the closed loop system. Our result follows from the application of a separation principle applicable to a class of sampled-data nonlinear systems. It is shown that the output feedback scheme recovers the rate of convergence achieved under state feedback receding horizon control for a sufficiently large observer gain and sampling frequency.; Moreover, a method is proposed for the adaptive receding horizon control of nonlinear systems. The method uses input to state stabilizing control Lyapunov functions to ensure stability. The adaptive receding horizon scheme is robust with respect to parameter estimation error and guarantees closed loop stability, provided a form of persistency of excitation condition is satisfied.; Simulation examples are provided to illustrate the applicability of both the output feedback scheme and adaptive scheme.