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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
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.
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.
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Appears in Collections:Conference Paper

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