Sensorless Control of PMSM Fractional Horsepower Drives by Signal Injection and Neural Adaptive-Band Filtering

This paper presents a sensorless technique for permanent-magnet synchronous motors (PMSMs) based on high-frequency pulsating voltage injection. Starting from a speed estimation scheme well known in the literature, this paper proposes the adoption of a neural network (NN) based adaptive variable-band filter instead of a fixed-bandwidth filter, needed for catching the speed information from the sidebands of the stator current. The proposed NN filter is based on a linear NN adaptive linear neuron (ADALINE), trained with a classic least mean squares (LMS) algorithm, and is twice adaptive. From one side, it is adaptive in the sense that its weights are adapted online recursively. From another side, its bandwidth is made adaptive during the running of the drive, acting directly on the learning rate of the NN filter itself. The immediate consequence of adopting a variable-band structure is the possibility to enlarge significantly the working speed range of the sensorless drive, which can be increased by a factor of five. The proposed observer has been tested experimentally on a fractional horsepower PMSM drive and has been compared also with a fixed-bandwidth structure.