Neural Networks Based Identification and Control of a Large Flexible Antenna

  • Sasaki, Minoru (Department of Human and Information Systems Engineering, Gifu University) ;
  • Murase, Takuya (Department of Human and Information Systems Engineering, Gifu University) ;
  • Ukita, Nobuharu (National Astronomical Observatory of Japan)
  • Published : 2004.08.25

Abstract

This paper presents identification and control of a 10-m antenna via accelerometers and angle encoder data. Artificial Neural Networks can be used effectively for the identification and control of nonlinear dynamical system such as a large flexible antenna. Some identification results are shown and compared with the results of conventional prediction error method. And we use a neural network inverse model for control the large flexible antenna. In the neural network inverse model, a neural network is trained, using supervised learning, to develop an inverse model of the antenna. The network input is the process output, and the network output is the corresponding process input. The control results show the validation of the ANN approach for identification and control of the 10-m flexible antenna.

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