• DocumentCode
    468986
  • Title

    Adaptive PID decoupling control based on RBF neural network and its application

  • Author

    Zhang, Ming-Guang ; Wang, Zhao-gang ; Wang, Peng

  • Author_Institution
    Lanzhou Univ. of Technol., Lanzhou
  • Volume
    2
  • fYear
    2007
  • fDate
    2-4 Nov. 2007
  • Firstpage
    727
  • Lastpage
    731
  • Abstract
    An adaptive PID decoupling control strategy based on Radial Basis Function (RBF) neural network (NN) is presented in this paper for nonlinear multivariable system. Based on the theory of optimization in groups, the parameters such as proportion, integration and differentiation of PID controller are tuned on-line using the self-learning ability of RBFNN. And the corresponding decoupling control law is achieved by conventional PID control algorithm. Simulation results show that the dynamic decoupling and completely static decoupling are obtained, the closed loop system has the advantages of higher speed response and stronger robustness.
  • Keywords
    adaptive control; multivariable control systems; neurocontrollers; nonlinear control systems; radial basis function networks; three-term control; RBF neural network; adaptive PID decoupling control; closed loop system; nonlinear multivariable system; radial basis function; self-learning ability; Adaptive control; Closed loop systems; Control systems; MIMO; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Programmable control; Proportional control; Three-term control; Adaptive PID control; RBF neural network; decoupling control; nonlinear system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-1065-1
  • Electronic_ISBN
    978-1-4244-1066-8
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2007.4420764
  • Filename
    4420764