• DocumentCode
    3310644
  • Title

    Self-Tuning PID Controller Based on Quantum Swarm Evolution Algorithm

  • Author

    Huang, Yourui ; Qu, Liguo ; Tian, Yiming

  • Author_Institution
    Anhui Univ. of Sci. & Technol., Huainan
  • Volume
    6
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    401
  • Lastpage
    404
  • Abstract
    PID control schemes have been widely used in most of control system for a long time. However, it is still a very important problem how to determine or tune the PID parameters, because these parameters have a great influence on the stability and the performance of the control system. On the other hand, in the last ten years, quantum computing is attracted as one method which gives us suitable answers for optimization problems. This paper proposes a novel quantum swarm evolution algorithm, called a quantum-inspired swarm evolution algorithm (QSEA), which is based on the concept and principles of quantum computing. The proposed algorithm adopts quantum angle to express Q-bit and improved particle swarm optimization to update automatically. After the quantum-inspired swarm evolution algorithm is described, the experiment result on the parameters of PID controller is given to show its efficiency.
  • Keywords
    evolutionary computation; particle swarm optimisation; quantum computing; self-adjusting systems; stability; three-term control; particle swarm optimization; performance control system; proportional-integral-derivative controller; quantum angle; quantum-inspired swarm evolution algorithm; self-tuning PID controller; stability control system; Artificial intelligence; Automatic control; Biology computing; Control systems; Evolution (biology); Evolutionary computation; Particle swarm optimization; Quantum computing; Stochastic processes; Three-term control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.458
  • Filename
    4667867