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Please use this identifier to cite or link to this item: http://idr.iitbbs.ac.in/jspui/handle/2008/110
Title: IIR system identification using cat swarm optimization
Authors: Panda G.
Pradhan P.M.
Majhi B.
Keywords: Cat swarm optimization
IIR system
System identification
Issue Date: 2011
Citation: 149
Abstract: Conventional derivative based learning rule poses stability problem when used in adaptive identification of infinite impulse response (IIR) systems. In addition the performance of these methods substantially deteriorates when reduced order adaptive models are used for such identification. In this paper the IIR system identification task is formulated as an optimization problem and a recently introduced cat swarm optimization (CSO) is used to develop a new population based learning rule for the model. Both actual and reduced order identification of few benchmarked IIR plants is carried out through simulation study. The results demonstrate superior identification performance of the new method compared to that achieved by genetic algorithm (GA) and particle swarm optimization (PSO) based identification. � 2010 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.eswa.2011.04.054
http://10.10.32.48:8080/jspui/handle/2008/110
Appears in Collections:Research Publications

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