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http://dx.doi.org/10.5391/JKIIS.2003.13.3.334

Design and Implementation of Recurrent Time Delayed Neural Network Controller Using Fuzzy Compensator  

Lee, Sang-Yun (경남대학교 기계자동화공학부)
Shin, Woo-Jae (경남대학교 전기전자공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.13, no.3, 2003 , pp. 334-341 More about this Journal
Abstract
In this paper, we proposed a recurrent time delayed neural network(RTDNN) controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed recurrent time delayed neural network controller get a good response compare with a time delayed neural network(TDU) controller. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.
Keywords
neural network controller; fuzzy compensator; FLC; TDNN; RTDNN;
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