• DocumentCode
    265035
  • Title

    Hybrid genetic algorithm-swarm intelligence based tuning of continuously stirred tank reactor

  • Author

    Kantha, Aditya Sarjak ; Utkarsh, Ayush ; Kumar, J. Ravi

  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a hybrid model of particle swarm optimization and genetic algorithm for tuning of PID controller parameters for a concentration control of isothermal continuously stirred tank reactor which is generally used to carry out chemical reactions in an industry on a large scale. The time domain study of different methods for tuning of PID controller parameters were observed and it was found that PSO(Particle Swarm Optimization)performance was better than GA(Genetic Algorithm) but the hybrid of GA-PSO gave the best output results in the observation to control the concentration of isothermal continuous stirred tank reactor.
  • Keywords
    chemical reactions; chemical reactors; control engineering computing; control system synthesis; genetic algorithms; particle swarm optimisation; production engineering computing; swarm intelligence; three-term control; GA-PSO; PID controller parameter tuning; chemical reactions; concentration control; hybrid genetic algorithm-swarm intelligence based tuning; isothermal continuously stirred tank reactor; particle swarm optimization; Chemical reactors; Feeds; Genetic algorithms; Inductors; Isothermal processes; Optimization; Tuning; CSTR; GA; Hybrid GA-PSO; PID; PSO;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial and Information Systems (ICIIS), 2014 9th International Conference on
  • Conference_Location
    Gwalior
  • Print_ISBN
    978-1-4799-6499-4
  • Type

    conf

  • DOI
    10.1109/ICIINFS.2014.7036611
  • Filename
    7036611