A PROPOSAL OF ENHANSED NEURAL NETWORK CONTROLLERS FOR MULTIPLE CONTROL SYSTEMS

  • Nakagawa, Tomoyuki (Large Scale System Stages Eng. Lab., Graduate School of Eng., Tohoku University) ;
  • Inaba, Masaaki (Systems Development Laboratory, Hitachi, Ltd.) ;
  • Sugawara, Ken (Large Scale System Stages Eng. Lab., Graduate School of Eng., Tohoku University) ;
  • Yoshihara, Ikuo (Large Scale System Stages Eng. Lab., Graduate School of Eng., Tohoku University) ;
  • Abe, Kenichi (Large Scale System Stages Eng. Lab., Graduate School of Eng., Tohoku University)
  • Published : 1998.10.01

Abstract

This paper presents a new construction method of candidate controllers using Multi-modal Neural Network(MNN). To improve a control performance of multiple controller, we construct, candidate controllers which consist of MNN. MNN can learn more complicated function than multilayer neural network. MNN consists of preprocessing module and neural network module. The preprocessing module transforms input signals into spectra which are used as input of the following neural network module. We apply the proposed method to multiple control system which controls the cart-pole balancing system and show the effectiveness of the proposed method.

Keywords