Model-based Feedback Control via Control Integrated Observers

Today’s development of machine tools utilizes various simulation tools to design machines which are more cost and energy efficient, have higher dynamics, stiffness, and accuracies. In increasing extent, these simulation tools are currently interconnected and allow an interaction by defined interfaces. This leads to even more exact depictions of the reality and more complex machine models. In the case of machine behavior the first natural frequency limits the performance of machine tool axes. In order to predict the machine behavior during linear movements or machining simple models are sufficient. In this paper a rigid body simulation is installed as Kalman-Filter on a machine tool control and runs in real time. The estimated position and velocities of the Kalman-Filter are used to control the axis. The paper will present the model generation, adaption, and verification via modal analysis. To allow linear movements with the rigid body simulation the model matrices need to be updated in each time step. The implementation of the model updating and the resulting linear motion of the model bodies during the run time of the control will be explained. The achieved results and improvements are evaluated by the identification of the dynamic test rig behavior at different positions.