• DocumentCode
    2341327
  • Title

    Application of self-tuning control to complicated, non-linear system by using neural network

  • Author

    Liu, Sizing ; Zhou, Zhaoying ; Zhang, Zhongjun

  • Author_Institution
    Dept. of Precision Instrum., Tsinghua Univ., Beijing, China
  • fYear
    1994
  • fDate
    10-12 May 1994
  • Firstpage
    163
  • Abstract
    This paper is concerned with building a model of Artificial Neural Network Predictor (ANP) for the self-tuning adaptive system. The learning algorithm of ANN is proposed accompanying with the analysis of its control strategy. Here, it could perhaps provide the active idea to solve such difficulty problem that is about how to use self-tuning algorithm to control the non-linear, complicated system. The results have demonstrated that use of ANP in self-tuning control can provide the better performance than can be achieved using the general strategy
  • Keywords
    artificial intelligence; control system analysis; control system synthesis; learning (artificial intelligence); neural nets; nonlinear control systems; self-adjusting systems; Artificial Neural Network Predictor; learning algorithm; neural network; nonlinear system; nonlinear, complicated system; self-tuning adaptive system; self-tuning algorithm; self-tuning control; Adaptive control; Adaptive systems; Artificial neural networks; Automatic control; Control systems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Optimal control; Performance analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference, 1994. IMTC/94. Conference Proceedings. 10th Anniversary. Advanced Technologies in I & M., 1994 IEEE
  • Conference_Location
    Hamamatsu
  • Print_ISBN
    0-7803-1880-3
  • Type

    conf

  • DOI
    10.1109/IMTC.1994.352100
  • Filename
    352100