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Direct Controller for Nonlinear System Using a Neural Network

신경망을 이용한 비선형 시스템의 직접 제어

  • Bae, Ceol-Soo (Information and Communication Engineering, Kwandong University)
  • 배철수 (관동대학교 정보통신공학과)
  • Received : 2013.09.30
  • Accepted : 2013.12.05
  • Published : 2013.12.31

Abstract

This paper reports the direct controller for nonlinear plants using a neural network. The controller was composed of an approximate controller and a neural network auxiliary controller. The approximate controller provides rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not place too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network was trained and the system showed stable performance for the inputs it has been trained for. The simulation results showed that it was quite effective and could realize satisfactory control of the nonlinear system.

Keywords

complementary signal;direct controller;neural network;nonlinear system;RBF

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