IIR system identification using cat swarm optimization

Authors:
Ganapati Panda;Pyari Mohan Pradhan;Babita Majhi
Affiliations:
School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, India;School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, India;Department of Information Technology, ITER, SOA University Bhubaneswar, India
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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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.