Journal of the Institute of Electronics Engineers of Korea SC (전자공학회논문지SC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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(Design of Neural Network Controller for Contiunous-Time Chaotic Nonlinear Systems)

연속 시간 혼돈 비선형 시스템을 위한 신경 회로망 제어기의 설계

  • Published : 2002.01.01
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Abstract

This paper presents a design method of the neural network-based controller using an indirect adaptive control method to deal with an intelligent control for chaotic nonlinear systems. The proposed control method includes the identification and control Process for chaotic nonlinear systems. The identification process for chaotic nonlinear systems is an off-line process which utilizes the serial-parallel structure of multilayer neural networks and simple state space neural networks. The control process is an on-line process which uses the trained neural networks as the system model. An error back-propagation method was used for training of identification and control for chaotic nonlinear systems. The performance of the proposed neural network controller was evaluated by application to the Duffing equation and the Lorenz equation, and the proposed controller was compared with other neural network-based controllers by computer simulations.

본 논문에서는 혼돈 비선형 시스템의 지능 제어를 위해 간접 적응 제어 방식에 기초한 신경 회로망 제어기 설계 방법을 제안하였다. 제안된 제어 방법은 혼돈 비선형 시스템의 동정을 위해 다층 신경 회로망과 간단한 상태 공간 신경 회로망을 사용한 직-병렬 동정 구조를 이용하여 오프 라인으로 동정 과정을 수행하였으며, 학습된 혼돈 비선형 시스템에 대한 신경 회로망 모델을 사용하여 온 라인으로 제어를 수행하였다. 이때 혼돈 비선형 시스템의 동정 및 제어를 위한 학습 방법은 오차 역전파 방법을 사용하였다. 한편 본 논문에서 제안된 제어 방법을 연속 시간 혼돈 비선형 시스템인 Duffing 방정식과 Lorenz 방정식에 각각 적용하여 신경 회로망을 사용한 기존의 제어 방법과 컴퓨터 모의 실험을 통해 제어 성능을 비교 및 고찰하였다.

Keywords

References

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