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

2008/11/01 by Deepyaman Maiti, Maiti, Deepyaman, Amit Konar +1
Computer Science · Engineering · Mathematics · #Advanced Control Systems Design #FOS: Computer and information sciences #Fractional Differential Equations Solutions #Metaheuristic Optimization Algorithms Research #Other Computer Science (cs.OH) #cs.OH

paper · pdf · doi:10.48550/arxiv.0811.0077

IEEE Sponsored Conference on Computational Intelligence, Control And Computer Vision In Robotics & Automation

arxiv created 2008/11/01 · openalex publication_date 2008/11/01 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

System 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.

Citations

• Fractional Differential Equations

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