Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1434
Title: Control of nonlinear systems with a linear state-feedback controller and a modified neural network tuned by genetic algorithm
Authors: Lam, HK
Ling, SH
Iu, HHC
Yeung, CW
Leung, FHF 
Keywords: Feedback control
Genetic algorithms
Neural networks
Parameter estimation
Issue Date: 2007
Publisher: IEEE
Source: CEC 2007 : IEEE Congress on Evolutionary Computation, Singapore, 25–28 September 2007, p. 1614-1619 How to cite?
Abstract: This paper presents the control of nonlinear systems with a neural network. In the proposed neural network, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer. By using a genetic algorithm with arithmetic crossover and non-uniform mutation, the parameters of the proposed neural network can be tuned. Application examples are given to illustrate the merits of the proposed neural network.
URI: http://hdl.handle.net/10397/1434
ISBN: 1-4244-1340-0
Rights: © 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Appears in Collections:Conference Paper

Files in This Item:
File Description SizeFormat 
Linear state-feedback controller_07.pdf256.97 kBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

291
Last Week
1
Last month
Checked on May 1, 2016

Download(s)

398
Checked on May 1, 2016

Google ScholarTM

Check



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.