Robust Adaptive Control for High-Order Nonlinear Systems With Unknown Upper Bound Uncertainties Based on Fully Actuated System Approaches and Multi-Objective Optimization

This study focuses on the design of a robust adaptive (RA) controller and a robust adaptive tracking (RAT) controller for high-order nonlinear systems that have unknown upper bound time-varying uncertainties. Utilizing the high-order fully actuated (HOFA) system approaches and Lyapunov stability theory, the proposed RA and RAT controllers are capable of overcoming system uncertainties, while also automatically adjusting parameter estimates associated with the unknown upper bound uncertainties. The proposed controllers ensure that both the state of the closed-loop system and the estimation error of the parameter vector converge globally to a bounded ellipsoid. Furthermore, the degrees of freedom provided by the HOFA system method is utilized for regional pole assignment, and an objective function is designed to ensure stability and enhance system performance. Finally, the effectiveness and practicality of the proposed control method are demonstrated through simulation examples, including a two-link manipulator.