Proceedings of the 2nd Joint International Conference on Multibody System Dynamics
The aim of this work is to provide a thorough research on the implementation of some nonlinear Kalman Filters (KF) using multibody (MB) models and to compare their performances in terms of accuracy and computational cost. The filters considered in this study are the extended KF (EKF) in its continuous form, the unscented KF (UKF) and the spherical simplex unscented KF (SSUKF). Two different MB formulations are taken into consideration to convert the differential algebraic equations (DAE) of the MB model into the ordinary differential equations (ODE) required by the filters: the state-space reduction method known projection matrix–R method and the penalty formulation. Additionally, both implicit and explicit integration schemes are used to evaluate the impact of explicit integrators over implicit integrators, commonly employed in MB simulations, in terms of accuracy, stability and computational cost, commonly employed in MB simulations. However, state estimation through KFs is a closed-loop estimation correcting the model drift according to the difference between the predicted measurement and the actual measurement, what limits the interest in using implicit integrators. Performance comparisons of all the aforementioned nonlinear observers have been carried out in simulation on a 5-bar linkage. The mechanism parameters have been obtained from an experimental 5-bar linkage and the sensor characteristics from off-the-shelf sensors reproduce a realistic simulation. The results should highlight useful clues for the choice of the most suitable filters, MB formulations and integration schemes.