Soft Computing

, Volume 3, Issue 4, pp 200–205

Genetic least squares for system identification

  • K. Warwick
  • Y. -H. Kang
  • R. J. Mitchell
Original paper

DOI: 10.1007/s005000050070

Cite this article as:
Warwick, K., Kang, YH. & Mitchell, R. Soft Computing (1999) 3: 200. doi:10.1007/s005000050070

Abstract

The recursive least-squares algorithm with a forgetting factor has been extensively applied and studied for the on-line parameter estimation of linear dynamic systems. This paper explores the use of genetic algorithms to improve the performance of the recursive least-squares algorithm in the parameter estimation of time-varying systems. Simulation results show that the hybrid recursive algorithm (GARLS), combining recursive least-squares with genetic algorithms, can achieve better results than the standard recursive least-squares algorithm using only a forgetting factor.

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • K. Warwick
    • 1
  • Y. -H. Kang
    • 1
  • R. J. Mitchell
    • 1
  1. 1.Department of Cybernetics, University of Reading, Reading, RG6 6AY, UKGB