Rotor position estimation of a bearingless permanent magnet synchronus motor by machine learning techniques

In this testis project, developed at the university of Bologna at LAR (Laboratory of Automation and Robotics), is studied the reconstruction of the rotor attitude of Bearingless Permanent Magnet Synchronous Motor (BPMSM), by processing the output of six hall effect sensor using a neural network to improve an already existing model-based reconstruction algorithm.