NDLI: Design of controller for a class of uncertain nonlinear systems with input saturation

Content Provider	IEEE Xplore Digital Library
Author	Bo Xu Shurong Li
Copyright Year	2010
Description	Author affiliation: School of Information and Control Engineering, China University of Petroleum, Dongying, Shandong 257061, China (Bo Xu; Shurong Li)
Abstract	In actual systems, actuator saturation is a common phenomenon, which often severely restricts system dynamic performance and gives rise to instability. In order to reduce the effects of saturation, this paper presents an adaptive control method based on multilayer neural networks (MNNs) for a class of uncertain nonlinear systems with Brunovsky canonical form and input saturation. This controller is composed of a tracking controller and a saturation compensator. The saturation compensator is designed by MNNs which considers the network reconstruction error and the system's external disturbance. The adaptation laws are derived in the sense of Lyapunov function. The closed-loop system is uniformly ultimately bounded, which is proved by Lyapunov theory. The simulation example is given to illustrate the effectiveness of this method.
Starting Page	970
Ending Page	974
File Size	293915
Page Count	5
File Format	PDF
ISBN	9781424451814
DOI	10.1109/CCDC.2010.5498079
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Actuators Control engineering Neural networks Nonlinear control systems Control systems Uncertain nonlinear systems Nonlinear dynamical systems Nonlinear systems Adaptive control Petroleum Actuator saturation Multi-layer neural network
Content Type	Text
Resource Type	Article

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