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Hybrid Neural Network Controller Using Adaptation Algorithm

  • ManJun Cai
  • JinCun Liu
  • GuangJun Tian
  • XueJian Zhang
  • TiHua Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4491)

Abstract

Neural network controller using adaptation algorithm is a new and simple controller, in which a feedback network propagating the error is not required. So it can be applied to hardware easily. Nevertheless, our simulations show that while the order of controlled plant is high, some unstable phenomenon appear and we also find that sometimes the error is far from being satisfactory, although when the order of controlled plant is low. Moreover, the present adaptation algorithm can not solve this problem. In this paper we will give our derivation of adaptation algorithm used in the neural network controller and configuration of an adaptive neural network controller. Then give some simulation figures to illustrate defect for the new controller. Finally we will develop a hybrid neural network to solve the problem and improve the accuracy as well as reduce the cost to the least in the practical application.

Keywords

Neural Network Learning Rate Output Error Adaptation Algorithm Neural Network Controller 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • ManJun Cai
    • 1
  • JinCun Liu
    • 1
  • GuangJun Tian
    • 1
  • XueJian Zhang
    • 1
  • TiHua Wu
    • 1
  1. 1.College of Electrical Engineering, YanShan University, QinHuangDao 066004China

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