• DocumentCode
    1592904
  • Title

    Multi-agent Based Distributed Genetic Algorithm Applied to the Optimization of Self-Adaptive PID Parameters of Hydro-turbine

  • Author

    Meng Anbo ; Peng Xiangang ; Yin Hao

  • Author_Institution
    Guangdong Univ. of Technol., Guangzhou, China
  • fYear
    2012
  • Firstpage
    359
  • Lastpage
    363
  • Abstract
    It is often long time-consuming for applying the traditional genetic algorithm to the PID optimization of hydro-turbine governor. To address such issue, a multi-agent based distributed genetic algorithm (MAGA) is proposed. Based on establishment of the non-linear digital simulation model of generating units, a distributed mobile computing platform implementing MAGA is built using agent middle ware, on which, the optimization for the self-adaptive PID governor is performed under different operating conditions. The simulation results show that the proposed MAGA can not only obtain good optimization performance compared with the conventional genetic algorithm, but shorten the optimization time significantly. Apparently, the proposed method provides a new perspectives and solutions to solve the optimization problem of complex control system.
  • Keywords
    adaptive control; control engineering computing; digital simulation; genetic algorithms; hydraulic turbines; middleware; mobile computing; multi-agent systems; optimal control; three-term control; MAGA; PID optimization; agent middle ware; distributed mobile computing platform; hydro-turbine governor; multiagent based distributed genetic algorithm; nonlinear digital simulation model; optimum control parameters; self-adaptive PID parameters; Adaptation models; Computational modeling; Containers; Genetic algorithms; Load modeling; Optimization; Unified modeling language; JADE; Multi-agent System; Parallel genetic algorithm; Self-adaptive PID; Three-gorge generating units;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-1-4577-2120-5
  • Type

    conf

  • DOI
    10.1109/ISdea.2012.576
  • Filename
    6173222