• DocumentCode
    1798431
  • Title

    Two-loop PID control using PSO-RGA algorithm for solar heat pumps

  • Author

    Ching-Chih Tsai ; Kuei-I Tsai ; Shen-Chang Hsu ; Shun-Feng Su

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chung Hsing Univ., Taichung, Taiwan
  • Volume
    2
  • fYear
    2014
  • fDate
    13-16 July 2014
  • Firstpage
    728
  • Lastpage
    733
  • Abstract
    In this paper, a two-loop PID (proportional integral derivative) controller is presented for a class of solar water-source heat pump systems (SWSHPS), which provide warm water with desired temperature for a semiconductor factory. A combination of the well-known particle swarm optimization (PSO) and real-coded genetic algorithm (RGA) is proposed to off-line optimally find the controller parameters of the proposed control law. Through simulations, the two-loop PID control strategy is shown to be effective and robust against parameter variations. By comparing with two existing two-loop PID control strategies, the proposed two-loop PID controller, tuned by the new PSO-RGA algorithm, is shown to give superior transient performance, smaller steady-state errors and better robustness against parameter variations.
  • Keywords
    genetic algorithms; heat pumps; particle swarm optimisation; robust control; solar heating; three-term control; transients; PSO; PSO-RGA algorithm; SWSHPS; particle swarm optimization; proportional integral derivative controller; real-coded genetic algorithm; semiconductor factory; solar water-source heat pump system; steady-state error; transient performance; two-loop PID control; Abstracts; Heat pumps; Robustness; Solar heating; PID control; Real-coded Genetic algorithm(RGA); Solar water-source heat pump system (SWSHPS); particle swarm optimization (PSO); temperature control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
  • Conference_Location
    Lanzhou
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4799-4216-9
  • Type

    conf

  • DOI
    10.1109/ICMLC.2014.7009700
  • Filename
    7009700