Approximation of a Fractional Order System by an Integer Order Model Using Particle Swarm Optimization Technique

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dc.creatorMaiti, Deepyaman
dc.creatorKonar, Amit
dc.date2008-11-01
dc.date.accessioned2026-07-07T10:14:44Z
dc.date.available2026-07-07T10:14:44Z
dc.descriptionSystem identification is a necessity in control theory. Classical control theory usually considers processes with integer order transfer functions. Real processes are usually of fractional order as opposed to the ideal integral order models. A simple and elegant scheme is presented for approximation of such a real world fractional order process by an ideal integral order model. A population of integral order process models is generated and updated by PSO technique, the fitness function being the sum of squared deviations from the set of observations obtained from the actual fractional order process. Results show that the proposed scheme offers a high degree of accuracy.
dc.descriptionIEEE Sponsored Conference on Computational Intelligence, Control And Computer Vision In Robotics & Automation
dc.identifierhttps://arxiv.org/abs/0811.0077
dc.identifierhttp://arxiv.org/abs/0811.0077
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/172982
dc.subjectOther Computer Science
dc.titleApproximation of a Fractional Order System by an Integer Order Model Using Particle Swarm Optimization Technique
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