• DocumentCode
    684709
  • Title

    Implementation of controller optimization using S-function based metaheuristic algorithms

  • Author

    Letting, L.K. ; Munda, J.L. ; Hamam, Yskandar

  • Author_Institution
    Tshwane Univ. of Technol., Pretoria, South Africa
  • fYear
    2012
  • fDate
    7-9 Dec. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents general technique for implementing metaheuristic algorithms using S-Functions and its application in controller parameter optimization. The proposed method provides a suitable platform for parameter tuning in MATLAB/Simulink and PLECS software platforms. The proposed technique is suitable for exchanging optimization parameters when the objective function is not expressed in closed mathematical form. The S-Function based technique takes advantage of the software framework by embedding function calls of the optimization algorithm in callback methods which are executed at predefined time intervals. This leads to great improvement in algorithm efficiency in terms of simulation speed and ease of implementation. Validity of the proposed method is verified by implementing the particle swarm optimization algorithm (PSO) as an S-Function. The S-Function based PSO algorithm is applied to tune PI controllers for converter control in a doubly fed induction generator (DFIG) wind generation system.
  • Keywords
    PI control; asynchronous generators; control system synthesis; particle swarm optimisation; wind power plants; DFIG; MATLAB-Simulink; PI controller tuning; PLECS software platforms; PSO; S-function based metaheuristic algorithms; callback methods; controller parameter optimization; converter control; doubly fed induction generator; function call embedding; particle swarm optimization algorithm; wind generation system; controller; metaheuristic; parameter optimization; s-function;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Information Science and Control Engineering 2012 (ICISCE 2012), IET International Conference on
  • Conference_Location
    Shenzhen
  • Electronic_ISBN
    978-1-84919-641-3
  • Type

    conf

  • DOI
    10.1049/cp.2012.2295
  • Filename
    6755674