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; Hung Fat Frank Leung

doi:10.1109/CEC.2007.4424666

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
, Hung Fat Frank Leung

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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.

Original language	English
Title of host publication	2007 IEEE Congress on Evolutionary Computation, CEC 2007
Pages	1614-1619
Number of pages	6
DOIs	https://doi.org/10.1109/CEC.2007.4424666
Publication status	Published - 1 Dec 2007
Event	2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore Duration: 25 Sept 2007 → 28 Sept 2007

Conference

Conference	2007 IEEE Congress on Evolutionary Computation, CEC 2007
Country/Territory	Singapore
Period	25/09/07 → 28/09/07

ASJC Scopus subject areas

Artificial Intelligence
Software
Theoretical Computer Science

More information

10.1109/CEC.2007.4424666

http://hdl.handle.net/10397/1434

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 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.",

author = "Lam, \{H. K.\} and Ling, \{S. H.\} and Iu, \{H. H C\} and Yeung, \{C. W.\} and Leung, \{Hung Fat Frank\}",

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Lam, HK, Ling, SH, Iu, HHC, Yeung, CW & Leung, HFF 2007, Control of nonlinear systems with a linear state-feedback controller and a modified neural network tuned by genetic algorithm. in 2007 IEEE Congress on Evolutionary Computation, CEC 2007., 4424666, pp. 1614-1619, 2007 IEEE Congress on Evolutionary Computation, CEC 2007, Singapore, 25/09/07. https://doi.org/10.1109/CEC.2007.4424666

Control of nonlinear systems with a linear state-feedback controller and a modified neural network tuned by genetic algorithm. / Lam, H. K.; Ling, S. H.; Iu, H. H C et al.
2007 IEEE Congress on Evolutionary Computation, CEC 2007. 2007. p. 1614-1619 4424666.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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

Abstract

Conference

ASJC Scopus subject areas

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