Step response identification for a magnetic bearing system based on frequency-sampling filter model

The nature of the active magnetic bearing has many advantages over the conventional bearing, as its operation is energy efficient and potentially leads to cleaner and noise-free environment. However, the successful operation of an active magnetic bearing system requires an accurate mathematical model, because of its unstable characteristics, as well as its nature of being a multi-input and multi-output system. This paper presents a two-level control structure for the active magnetic bearing system. The analog proportional derivative (PD) controllers are used in the low-level, a supervision controller in the upper-level. In this application, the step response models of the plant are identified from experimental data using frequency sampling filter method. The comparison between the identified step responses and the measured step responses proves the efficacy of the frequency sampling filter approach.