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

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-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 languageEnglish
Title of host publication2007 IEEE Congress on Evolutionary Computation, CEC 2007
Pages1614-1619
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2007
Event2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
Duration: 25 Sep 200728 Sep 2007

Conference

Conference2007 IEEE Congress on Evolutionary Computation, CEC 2007
Country/TerritorySingapore
Period25/09/0728/09/07

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

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