Adaptive neural output feedback control for strict feedback nonlinear system
SUN Guo-fa
TIAN Yu
WANG Su-zhen
Abstract：Based on nonlinear feedback function, this paper investigates output feedback control problem for a class of nonlinear systems. In the case of systems with uncertain functions, nonlinear feedback neural network observer estimates system states in real time. Employing the obtained state signals, an adaptive neural network controller is designed to guarantee the stability of the closed-loop system and the boundedness of all signals. The desired closed-loop tracking performance can be achieved by adjusting the value of the design parameters. Numerical simulation results show that, without state transformation, the state observer overcomes the chattering problem caused by the output feedback sliding mode controller.
Keywords：state observerdynamic surface controlactive disturbance rejection controlneural network
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 375-382 )