Particle swarm optimization for chaotic system parameter estimation

B. Samanta, C. Nataraj

Research output: Contribution to book or proceedingConference articlepeer-review

3 Scopus citations

Abstract

A study is presented on the application of particle swarm optimization (PSO) for estimation of parameters in chaotic systems. The parameter estimation is formulated as a nonlinear optimization problem using PSO to minimize the synchronization error for the observable states of the actual system and its mathematical model. The procedure is illustrated using a typical chaotic system of Lorenz equations. The effectiveness of different variants of PSO on parameter estimation is studied with a wide search range of parameters.The results show the capability of the proposed PSO based approach in estimating the chaotic system parameters even in the presence of observation noise.

Original languageEnglish
Title of host publication2009 IEEE Swarm Intelligence Symposium, SIS 2009 - Proceedings
Pages74-80
Number of pages7
DOIs
StatePublished - 2009
Event2009 IEEE Swarm Intelligence Symposium, SIS 2009 - Nashville, TN, United States
Duration: Mar 30 2009Apr 2 2009

Publication series

Name2009 IEEE Swarm Intelligence Symposium, SIS 2009 - Proceedings

Conference

Conference2009 IEEE Swarm Intelligence Symposium, SIS 2009
Country/TerritoryUnited States
CityNashville, TN
Period03/30/0904/2/09

Scopus Subject Areas

  • Artificial Intelligence
  • Computer Science Applications
  • Software

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