Identification of system parameters and external forces in AMB-supported PMSM system

Abstract

Active magnetic bearings (AMBs) have unique superiority in vibration reduction and nowadays have been widely used in permanent magnet synchronous motor (PMSM). To maximize the advantage of AMBs, an accurate model of the total system is indispensable in controller design. This paper proposes a two-step identification algorithm for an AMB-supported PMSM system, in which the AMB model remains its nonlinear characteristics and the unbalance magnetic pull (UMP) in PMSM is covered. The proposed identification procedure contains two steps: suspension identification for the AMB-rotor system and steady-rotation-identification for external forces. In simulation verification, the algorithm shows robustness to measure noise in sensors and inertia in amplifiers. The algorithm is also carried out on an industrial AMB-supported PMSM test rig. To validate the identification results, the identified values are applied on a Simulink model of the system, from which the response under condition of designed excitations, steady-rotation state at various rotational speeds and a run-up procedure is generated. The simulation results and the experimental measurements show close agreement with each other, which verifies the accuracy of the identification method.