Robustness Analysis of Two-Mass System Control Using Acceleration-Aided Kalman Filter

For fast and precise motion control, the robustness against disturbances and/or system uncertainties is one of essential factors. In many industrial applications, there is a typical situation that the non-collocated mass position can not be measured because of cost limitations and/or manufacturing issues. The robustness and the control performance usually deteriorates compared to the case that all state variables are measurable. To solve this problem, the acceleration-aided Kalman filter (aaKF) using a MEMS accelerometer has been proposed. In this paper, the robustness improvement by the aaKF is analyzed based on the idea of loop transfer recovery. Analysis and simulation results show that reliable measurements of load-side acceleration improve the estimation of load-side information and the robustness of the control system implementing an optimal feedback. The utility of the aaKF in a two-mass system is confirmed from experiments.