On-Line Speed Estimation based on ANN for PMSM Sensorless Speed Control

B. Sahhary and H. Abbas (Germany)


Sensorless speed control, ANN-MRAS, Modelling of the PMSM, artificial neural network.


This paper proposes a method for on-line speed estimation of a permanent magnet synchronous motor (PMSM) based on an artificial neural network (ANN), where, the conventional Model Reference Adaptive system (MRAS), which is usually used to estimate the rotor speed of the PMSM, is represented by an ANN. The ANN contains adjustable and constant weights. The adjustable weights are proportional to the rotor speed. The adjustable weights are changed by using the error between the outputs of the reference model and the ANN, which is the PMSM’s output active power, since any mismatch between the actual and the estimated rotor speeds results in an error between the mentioned outputs. The steepest decent method is used to adjust on-line the weights of the ANN. Experimental and simulation results illustrate the practicality of the proposed method.

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