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Satellite attitude tracking using optimal neuro-controller

Meghdari, A ; Sharif University of Technology | 2003

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  1. Type of Document: Article
  2. DOI: 10.1109/AERO.2003.1235191
  3. Publisher: 2003
  4. Abstract:
  5. In this paper, a new control strategy for optimal attitude tracking control of a multivariable satellite system has been presented. The approach is based on a Multilayer Perceptron Neural Network (MLPNN) and a classical PD Controller for its initial stabilization. It is shown how the network can be employed as a multivariable self-organizing and self-learning controller in conjunction with a PD controller for attitude control of a satellite. By using three thrusters and quaternion for kinematics representation, the attitude dynamics of the satellite has been presented. In contrast to the previous classical approaches, it is shown how this controller can be carried out in an on-line manner with adaptive learning capabilities. The problem of robustness, accuracy and speed of response has all been addressed and through an example, the applicability of the proposed control scheme is illustrated. © 2003 IEEE
  6. Keywords:
  8. Source: 2003 IEEE Aerospace Conference, Big Sky, MT, 8 March 2003 through 15 March 2003 ; Volume 6 , 2003 , Pages 2663-2669 ; 1095323X (ISSN); 078037651X (ISBN); 9780780376519 (ISBN)
  9. URL: https://ieeexplore.ieee.org/abstract/document/1235191