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Estimation of States and Parameters in Chaotic Systems Using Particle Swarm Optimization

[+] Author Affiliations
B. Samanta, C. Nataraj

Villanova University, Villanova, PA

Paper No. DETC2009-87535, pp. 651-659; 9 pages
doi:10.1115/DETC2009-87535
From:
  • ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1: 22nd Biennial Conference on Mechanical Vibration and Noise, Parts A and B
  • San Diego, California, USA, August 30–September 2, 2009
  • Conference Sponsors: Design Engineering Division and Computers in Engineering Division
  • ISBN: 978-0-7918-4898-2 | eISBN: 978-0-7918-3856-3
  • Copyright © 2009 by ASME

abstract

A study is presented on the application of particle swarm optimization (PSO) for estimation of states and 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. Results are presented to study the effects of different observable system states and observation noise on parameter estimation. The effectiveness of different variants of PSO on parameter estimation is also studied. The results show the capability of the proposed PSO based approach in estimating the chaotic system parameters with wide search range (50–200%) and in the presence of observation noise.

Copyright © 2009 by ASME

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