Adaptive Approximation-Based Control for Nonlinear Systems: A Unified Solution with Accurate and Inaccurate Measurements

Abstract

A unified solution to adaptive approximation-based control for nonlinear systems with accurate and inaccurate state measurement is synthesized in this study. Starting from the standard adaptive approximation-based controller with accurate state measurement, its corresponding physical interpretation, stability conclusion, and learning ability are rigorously addressed when facing additive measurement inaccuracy, and explicit answers are obtained in the framework of both controller matching and system matching. Finally, it proves that, with a certain condition, the standard adaptive approximation-based controller works as a unified solution for the cases with accurate and inaccurate measurement, and the solution can be extended to the nonlinear system control problems with extra unknown dynamics or faults in actuator and/or process dynamics. A single-link robot arm example is used for the simulation demonstration of the unified solution.