Hammerstein model identification based on bacterial foraging

1 January 2006

journal article
Published by Institution of Engineering and Technology (IET) in Electronics Letters

Vol. 42 (23), 1332-1334
https://doi.org/10.1049/el:20062743

Abstract

A new algorithm for Hammerstein model identification based on bacterial foraging is developed. Simulations and comparisons show its advantages over the particle swarm optimisation algorithm in terms of immunity to coloured noise, model accuracy, and the convergence of parameters.

Keywords

MODEL ACCURACY
COLOURED NOISE IMMUNITY
HAMMERSTEIN MODEL IDENTIFICATION
BACTERIAL FORAGING
PARTICLE SWARM OPTIMISATION

This publication has 2 references indexed in Scilit:

A new optimizer using particle swarm theory
Published by Institute of Electrical and Electronics Engineers (IEEE) ,2002
Biomimicry of bacterial foraging for distributed optimization and control
IEEE Control Systems, 2002

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