Multi-Layer Nonlinear Extended Kalman Filters for Two-Mass Drive System Parameters Identification

In this paper, the concept of an estimator of the parameters of the two-mass drive system is presented. Significant changes in parameters, such as the load-side time constant, can lead to large estimation errors and compromised closed-loop performance in drives with an elastic shaft. The proposed multi-layer estimators use multiple internal nonlinear extended Kalman filters (EKF) to enhance the accuracy of state estimation. After a theoretical introduction, different structures were studied with simulation tests conducted in MATLAB/Simulink (2010a) and the effect of the number of filters was presented. The results show that the use of multi-layer observers can improve state estimation and accelerate online identification compared to classical methods. The results are confirmed by experimental validation carried out using dSPACE 1103.