Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2007.07a
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- Pages.1730-1731
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- 2007
Direct Adaptive Control Based on Neural Networks Using An Adaptive Backpropagation Algorithm
적응 역전파 학습 알고리즘을 이용한 신경회로망 제어기 설계
- Choi, Kyoung-Mi (Department of Electrical and Electronic Engineering, Yonsei University) ;
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Choi, Yoon-Ho
(Department of Electronic Engineering, Kyonggi University) ;
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Park, Jin-Bae
(Department of Electrical and Electronic Engineering, Yonsei University)
- Published : 2007.07.18
Abstract
In this paper, we present a direct adaptive control method using neural networks for the control of nonlinear systems. The weights of neural networks are trained by an adaptive backpropagation algorithm based on Lyapunov stability theory. We develop the parameter update-laws using the neural network input and the error between the desired output and the output of nonlinear plant to update the weights of a neural network in the sense that Lyapunove stability theory. Beside the output tracking error is asymptotically converged to zero.
Keywords