• DocumentCode
    2658533
  • Title

    Advanced particle swarm optimization-based PID controller parameters tuning

  • Author

    Jalilvand, Abolfazl ; Kimiyaghalam, Ali ; Ashouri, Ahmad ; Mahdavi, Meisam

  • Author_Institution
    Dept. of Electr. Eng., Zanjan Univ., Zanjan
  • fYear
    2008
  • fDate
    23-24 Dec. 2008
  • Firstpage
    429
  • Lastpage
    435
  • Abstract
    PID parameter optimization is an important problem in control field. Particle swarm optimization (PSO) is powerful stochastic evolutionary algorithm that is used to find the global optimum solution in search space. However, it has been observed that the standard PSO algorithm has premature and local convergence phenomenon when solving complex optimization problem. To resolve this problem an advanced particle swarm optimization (APSO) is proposed in this paper. This new algorithm is proposed to augment the original PSO searching speed. This study proposes to use the (APSO) for its fast searching speed. These advanced particle swarm optimization to accelerate the convergence. The algorithms are simulated with MATLAB programming. The simulation result shows that the PID controller with (APSO) has a fast convergence rate and a better dynamic performance.
  • Keywords
    evolutionary computation; mathematics computing; particle swarm optimisation; stochastic systems; three-term control; MATLAB programming; PID controller; PID parameter optimization; advanced particle swarm optimization; parameters tuning; stochastic evolutionary algorithm; Artificial intelligence; Control systems; Convergence; Evolutionary computation; Genetic algorithms; PD control; Particle swarm optimization; Pi control; Proportional control; Three-term control; Advanced PSO Algorithm; Genetic Algorithm; PID Parameters Tuning; Parameter Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multitopic Conference, 2008. INMIC 2008. IEEE International
  • Conference_Location
    Karachi
  • Print_ISBN
    978-1-4244-2823-6
  • Electronic_ISBN
    978-1-4244-2824-3
  • Type

    conf

  • DOI
    10.1109/INMIC.2008.4777776
  • Filename
    4777776