Wavelet Reduced-Order Observer-based Adaptive Tracking Control for a Class of Uncertain Nonlinear Systems

Abstract

This Paper investigates the mean to design the reduced-order observer and observer-based controllers for a class of uncertain nonlinear systems. A new design approach of wavelet-based adaptive reduced-order observer is proposed. The proposed wavelet adaptive reduced-order observer performs the task of identification of unknown system dynamics in addition to the reconstruction of states of the system. Owing to their superior learning capabilities, wavelet networks are employed in this work for the purpose of identification of unknown system dynamics. Using the feedback control, based on reconstructed states, the behavior of closed-loop system is investigated. A numerical example is provided to verify the effectiveness of theoretical development .

Keywords: Wavelet neural networks, reduced order observer, adaptive control, Lyapunov functional