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dc.contributor.authorOzdemir, Mahmut T. and Ozturk, Dursun and Eke, Ibrahim and Celik, Vedat and Lee, Kwang Y.
dc.date.accessioned2021-04-02T12:03:50Z
dc.date.available2021-04-02T12:03:50Z
dc.date.issued2015
dc.identifier10.1016/j.ifacol.2015.12.429
dc.identifier.issn2405-8963
dc.identifier.urihttp://acikerisim.bingol.edu.tr/handle/20.500.12898/2581
dc.description.abstractParticle Swarm Optimization algorithm converges rapidly during the initial stage of a global search, but around global optimum, the search process slows down. In order to overcome this problem and to further enhance the performance of Particle Swarm Optimization. this paper implements a hybrid algorithm. Bacterial Swarm Optimization, combining the features of Bacterial Foraging Optimization and Particle Swarm Optimization The PID parameters of classical and fractional-order controllers are optimized with Bacterial Swann Optimization for load frequency control of a two area power system. Simulation results show fractional-order PID controller has less settling time and less overshoot than the classical PID controller for most of studies. (C) 2015, IFAC (International Rderation or Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
dc.language.isoEnglish
dc.sourceIFAC PAPERSONLINE
dc.titleTuning of Optimal Classical and Fractional Order PID Parameters forAutomatic Generation Control Based on the Bacterial Swarm Optimization
dc.typeProceedings Paper


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