대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 1998년도 하계학술대회 논문집 B
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- Pages.740-743
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- 1998
비선형 시스템 제어를 위한 동적 신경망의 최적화
Optimization of Dynamic Neural Networks for Nonlinear System control
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Ryoo, Dong-Wan
(Dept. of Electrical Eng. Kyungpook Nat. Univ.) ;
- Lee, Jin-Ha (Dept. of Electrical Eng. Kyungpook Nat. Univ.) ;
- Lee, Young-Seog (Dept. Electrical Eng. Yeunghin Jouior College) ;
- Seo, Bo-Hyeok (Dept. of Electrical Eng. Kyungpook Nat. Univ.)
- 발행 : 1998.07.20
초록
This paper presents an optimization algorithm for a stable Dynamic Neural Network (DNN) using genetic algorithm. Optimized DNN is applied to a problem of controlling nonlinear dynamical systems. DNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDNN has considerably fewer weights than DNN. The object of proposed algorithm is to the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling, a nonlinear dynamic system using the proposed optimized SDNN considering stability' is demonstrated by case studies.
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