Title :
Neural network-based sliding mode control for a class of uncertain systems with measurement noise
Author :
Jinyong, Yang ; Yingmin, Jia
Author_Institution :
Seventh Res. Div., Beijing Univ. of Aeronaut. & Astronaut., China
Abstract :
In this paper, we consider sliding mode control (SMC) of uncertain systems whose output is contaminated by external disturbances. The cone-bounded assumption on uncertainties is removed via neural networks. The proposed sliding-mode controller can not only guarantee a uniform ultimate boundedness of states of the plant, but also the boundedness of all other signals in the closed-loop system.
Keywords :
closed loop systems; neural nets; nonlinear systems; uncertain systems; variable structure systems; closed-loop system; measurement noise; neural network-based sliding mode control; nonlinear systems; uncertain systems; Adaptive control; Control systems; Extraterrestrial measurements; Measurement uncertainty; Neural networks; Noise measurement; Pollution measurement; Programmable control; Sliding mode control; Uncertain systems;
Conference_Titel :
TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Print_ISBN :
0-7803-7490-8
DOI :
10.1109/TENCON.2002.1182608
