제어로봇시스템학회:학술대회논문집

제어로봇시스템학회 (Institute of Control, Robotics and Systems)
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Differential Geometric Conditions for the state Observation using a Recurrent Neural Network in a Stochastic Nonlinear System

  • Seok, Jin-Wuk (Real-Time Multimedia Research Team Embedded S/W Technology Center Computer and Software Technology Laboratory Electronics and Telecommunications Research Institute) ;
  • Mah, Pyeong-Soo (Real-Time Multimedia Research Team Embedded S/W Technology Center Computer and Software Technology Laboratory Electronics and Telecommunications Research Institute)
  • 발행 : 2003.10.22
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초록

In this paper, some differential geometric conditions for the observer using a recurrent neural network are provided in terms of a stochastic nonlinear system control. In the stochastic nonlinear system, it is necessary to make an additional condition for observation of stochastic nonlinear system, called perfect filtering condition. In addition, we provide a observer using a recurrent neural network for the observation of a stochastic nonlinear system with the proposed observation conditions. Computer simulation shows that the control performance of the stochastic nonlinear system with a observer using a recurrent neural network satisfying the proposed conditions is more efficient than the conventional observer as Kalman filter

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