Title :
Comparative study on dynamic identification of parallel motion platform for a novel flight simulator
Author :
Wu, Dongsu ; Gu, Hongbin ; Li, Peng
Author_Institution :
Coll. of Civil Aviation, Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
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.
Keywords :
Kalman filters; aerospace simulation; least squares approximations; motion control; nonlinear control systems; parameter estimation; Bayesian type filters; Gaussian mixture sigma point particle filter; extended Kalman filter; flight simulator; least squares estimation; nonlinear system; parallel motion platform; parameter identification approach; particle filter; unscented Kalman filter; Aerodynamics; Aerospace simulation; Costs; Error correction; Least squares approximation; Manipulator dynamics; Nonlinear dynamical systems; Parallel robots; Parameter estimation; Vehicle dynamics;
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-4774-9
Electronic_ISBN :
978-1-4244-4775-6
DOI :
10.1109/ROBIO.2009.5420471
