The Journal of Korea Institute of Information, Electronics, and Communication Technology (한국정보전자통신기술학회논문지)
- Volume 5 Issue 1
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- Pages.7-12
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- 2012
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- 2005-081X(pISSN)
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- 2288-9302(eISSN)
DOI QR Code
Direct Controller for Nonlinear System Using a Neural Network
- Bae, Cheol-Soo ;
- Park, Young-Cheol ;
- Nam, Kee-Hwan ;
- Kang, Yong-Seok ;
- Kim, Tae-Woo ;
- Hwang, Suen-Ki ;
- Kim, Hyon-Yul ;
- Kim, Moon-Hwan
- 배철수 (관동대학교 의료공학과) ;
- 박영철 (관동대학교 정보통신공학과) ;
- 남기환 ((주)삼형전자) ;
- 강용석 (한국폴리텍III대학) ;
- 김태우 (한국폴리텍III대학) ;
- 황선기 (한국폴리텍IV대학) ;
- 김현열 (관동대학교 정보통신공학과) ;
- 김문환 (한국전파기지국(주) 기술연구소)
- Received : 2011.12.20
- Accepted : 2012.01.20
- Published : 2012.02.29
Abstract
In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller. The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.