제어로봇시스템학회:학술대회논문집
- 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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- Pages.70-70
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- 2000
Design of Neuro-Fuzzy Controllers for DC Motor Systems with Friction
- Kim, Min-Jae (School of Electronic and Electrical engineering, Kyungpook National University) ;
- Jun oh Jang (Department of Computer Control Engineering, Uiduk University) ;
- Jeon, Gi-Joon (School of Electronic and Electrical engineering, Kyungpook National University)
- 발행 : 2000.10.01
초록
Recently, a neuro-fuzzy approach, a combination of neural networks and fuzzy reasoning, has been playing an important role in the motor control. In this paper, a novel method of fiction compensation using neuro-fuzzy architecture has been shown to significantly improve the performance of a DC motor system with nonlinear friction characteristics. The structure of the controller is the neuro-fuzzy network with the TS(Takagi-Sugeno) model. A back-propagation neural network based on a gradient descent algorithm is employed, and all of its parameters can be on-line trained. The performance of the proposed controller is compared with both a conventional neuro-controller and a PI controller.