Nonlinear systems design by a novel fuzzy neural system via hybridization of em and PSO algorithms

Ching Hung Lee*, Jun Hao Liang, Yu Chia Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, we propose a hybridization of electromagnetism-like mechanism (EM) and particle swarm optimization algorithm (PSO) algorithms to design the proposed functional-link based Petri recurrent fuzzy neural system (FLPRFNS) for application of nonlinear system control. The FLPRFNS has a TSK-type fuzzy consequent part which uses functional-link based orthogonal basis functions and a Petri layer is added to eliminate the redundant fuzzy rule for each input. In addition, the FLPRFNS is trained by a hybrid algorithm-modified EMPSO. The main modification is that the randomly neghiborhoodly local search is replaced by particle swarm optimization algorithm with an instant update particles velocity strategy. Each particle updates its velocity instantaneously one by one and every particle can get best information from system. The modified EMPSO combines the advantages of multipoint search, global optimization, and faster convergence. Simulation results show that the modified EMPSO has the ability of golbal optimization, advantages of faster convergence and FLPRFNS has effect of higher accuracy.

Original languageEnglish
Title of host publicationProceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010
Pages19-24
Number of pages6
StatePublished - 2010
EventInternational MultiConference of Engineers and Computer Scientists 2010, IMECS 2010 - Kowloon, Hong Kong
Duration: 17 Mar 201019 Mar 2010

Publication series

NameProceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010

Conference

ConferenceInternational MultiConference of Engineers and Computer Scientists 2010, IMECS 2010
Country/TerritoryHong Kong
CityKowloon
Period17/03/1019/03/10

Keywords

  • Electromagnetism-like mechanism
  • Functional link
  • Fuzzy neural system
  • Particle swarm optimization
  • Petri net

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