Control of nonlinear systems with a linear state-feedback controller and a modified neural network tuned by genetic algorithm

H K Lam; S H Ling; H H C Iu; C W Yeung; F H F Leung

Control of nonlinear systems with a linear state-feedback controller and a modified neural network tuned by genetic algorithm

H K Lam, S H Ling, H H C Iu, C W Yeung, F H F Leung

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

Abstract

This paper presents the control of nonlinear 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

Original language	English
Title of host publication	2007 Ieee Congress on Evolutionary Computation, Vols 1-10, Proceedings
Place of Publication	NEW YORK
Publisher	IEEE
Pages	1614 - 1619
Number of pages	6
ISBN (Print)	978-1-4244-1339-3
Publication status	Published - 2007
Event	IEEE Congress on Evolutionary Computation - Singapore, Singapore Duration: 1 Jan 2007 → …

Conference

Conference	IEEE Congress on Evolutionary Computation
Country/Territory	Singapore
City	Singapore
Period	1/01/2007 → …

Cite this

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title = "Control of nonlinear systems with a linear state-feedback controller and a modified neural network tuned by genetic algorithm",

abstract = "This paper presents the control of nonlinear 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",

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T1 - Control of nonlinear systems with a linear state-feedback controller and a modified neural network tuned by genetic algorithm

AU - Lam, H K

AU - Ling, S H

AU - Iu, H H C

AU - Yeung, C W

AU - Leung, F H F

PY - 2007

Y1 - 2007

N2 - This paper presents the control of nonlinear 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

AB - This paper presents the control of nonlinear 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

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M3 - Conference paper

SN - 978-1-4244-1339-3

SP - 1614

EP - 1619

BT - 2007 Ieee Congress on Evolutionary Computation, Vols 1-10, Proceedings

PB - IEEE

CY - NEW YORK

T2 - IEEE Congress on Evolutionary Computation

Y2 - 1 January 2007

ER -

Control of nonlinear systems with a linear state-feedback controller and a modified neural network tuned by genetic algorithm

Abstract

Conference

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