• DocumentCode
    3157785
  • Title

    Parameter optimization of model predictive control using PSO

  • Author

    Susuki, Ryohei ; Kawai, Fukiko ; Nakazawa, Chikashi ; Matsui, Tetsuro ; Aiyoshi, Eitaro

  • Author_Institution
    Grad. Sch. of Sci. & Technol., Keio Univ., Yokohama
  • fYear
    2008
  • fDate
    20-22 Aug. 2008
  • Firstpage
    1981
  • Lastpage
    1988
  • Abstract
    Among various control methods, model predictive control (MPC) becomes one of the major control strategies and has many successful applications. This paper presents an automatic tuning method of MPC using particle swarm optimization (PSO). One of the challenges in MPC is how the control parameters can be tuned for various target plants, and usage of PSO for automatic tuning is one of the solutions. The tuning problem of MPC is formulated as an optimization problem and PSO is applied as the optimization techniques. PSO is one of meta-heuristic methods which are known to search a global optimum at a relatively high ratio and with no use of a gradient. The numerical results for simple examples show the effectiveness of the proposed PSO-based automatic tuning method.
  • Keywords
    particle swarm optimisation; predictive control; automatic tuning; control parameter; metaheuristic method; model predictive control; parameter optimization; particle swarm optimization; Automatic control; Electronic mail; Feedback control; Feeds; Guidelines; Optimal control; Optimization methods; Particle swarm optimization; Predictive control; Predictive models; feed back system; model predictive control; particle swarm optimizaiton;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE Annual Conference, 2008
  • Conference_Location
    Tokyo
  • Print_ISBN
    978-4-907764-30-2
  • Electronic_ISBN
    978-4-907764-29-6
  • Type

    conf

  • DOI
    10.1109/SICE.2008.4654987
  • Filename
    4654987