Simulative Investigation of Transfer Function-based Disturbance Observer for Disturbance Estimation on Electromechanical Axes

摘要

In the field of machine tools, applicable solutions for monitoring process forces are becoming increasingly important. In addition to sensor-based approaches there are also methods which utilize the already available signals of the machine control. Usually, the motor currents and, when applicable, position values of the feed axes are considered. By applying reduced order models of the machine axes, non-process components are subtracted from the measured signals. However, these approaches are often utilizing simplified models or require additional a-priori knowledge, for example construction data or actual parameter values. The former in particular has a negative impact on the quality of the estimations. To overcome these disadvantages, this paper presents a novel observer structure based on the mechanical system transfer function of the feed axis. One main advantage is achieved by applying scalable and automatically generated models with focus on distinct frequency ranges. All necessary information is provided by a frequency response of the speed control plant, as it is typically obtained during the commissioning phase of electromechanical feed axes. By inverting the system transfer function and considering an additional disturbance transfer function, the quality of the estimation can be significantly improved compared to previous approaches.