Comparative study on dynamic identification of parallel motion platform for a novel flight simulator

  • Authors:

  • Dongsu Wu;Hongbin Gu;Peng Li

  • Affiliations:

  • College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China;College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China;College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China

  • Venue:
  • ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
  • Year:
  • 2009

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Abstract

This paper investigates theoretical and experimental comparison of LS estimation and Bayesian type filters such as EKF, UKF, PF and GMSPPF (Gaussian Mixture Sigma Point Particle Filter) methods for dynamic identification of a 6-DOF parallel motion platform. Comparison results show that the UKF method and the GMSPPF method are most efficient and easy-to-use parameter identification approaches for highly nonlinear system.