Cooperative control of an active magnetic bearing and sensorless drive system

Abstract

This thesis presents the cooperative control of an active magnetic bearing (AMB) and sensorless drive system. Traditionally, these two systems are considered as independent modular components within a larger system. The control of both systems requires angular speed information. Principally, the speed is required in the unbalance control of the AMB and the speed control of the drive. Furthermore, the speed is also required in both systems to compute cross-coupling terms for feed forward cancellation. Historically, the speed is estimable in both systems, but only above a threshold speed. The speed estimation in the AMB relied on the orbit generated due to unbalance. The speed estimation of the sensorless drive (of a surface mounted PMSM) relied upon the generated back-emf. This resulted in the sensorless drive system requiring an open-loop start-up procedure. It has been found by utilizing a novel method which relies on the disturbance force on the rotor, due to unbalanced magnetic pull, that it is possible for the AMB system to estimate the angular position of the rotor from standstill up to an upper limit in speed. Sharing this estimated angular position with the drive system, it is possible to skip the open-loop start-up of the drive and start it in vector controlled mode. The drive is switched to sensorless drive mode before the angular position accuracy upper limit is reached. After this switch over, the estimated angle by the sensorless vector control is in turn shared with the AMB system for unbalance control. The sensorless drive control algorithm has been reorganized to integrate in such a manner with the AMB’s estimated angular position so that a smooth bump less transfer results during the switch over. The main contributions of this work are the disturbance force model identification by the AMB system for estimation of the angular position and the supervisory coordination of the two controlled systems to act cooperatively. The key structure proposed for consolidation of the shared state information between the two systems is by integration into a phase-locked loop (PLL)