Nonlinear Feedback Design for Observer-based Neural Adaptive Dynamic Surface Control of MIMO Uncertain Nonlinear Systems

摘要

This talk presents an observer-based neural adaptive dynamic surface control for MIMO uncertain nonlinear systems based on a nonlinear feedback technique, which tries to combine the merits of high gain feedback and low gain feedback in an easily manner. The core idea of such technique is that the feedback gain holds nonlinear mapping relationship with system states, which is achieved by a continuous differentiable nonlinear gain function. Caused by the compound property of nonlinear gain feedback, a non-quadratic Lyapunov function is designed to prove the closed-loop stability. Comparative results are shown to verify the effectiveness.