Title :
Sensorless control of PMSM using a new efficient neural network speed estimator
Author :
Sperb, Elisabeth C L ; Negri, Lucas H. ; Baasch, Anna K S ; Polli, Horácio B. ; De Oliveira, José ; Nied, Ademir
Author_Institution :
Dept. of Electr. Eng., Santa Catarina State Univ., Joinville, Brazil
Abstract :
In order to reduce the cost and improve the reliability of variable speed drives, sensorless techniques for estimation rotor speed from measurement of voltage and current have been the subject of intensive research. This paper proposes a sensorless control strategy for Permanent Magnet Synchronous Motor (PMSM) control using a novel neural network algorithm. The proposed observer uses a neural network trained to learn the electrical and mechanical motor models using the current prediction error. Experiments were performed, showing that the proposed network topology and training algorithm have advantages to the classical ones currently employed in sensorless control.
Keywords :
electric current measurement; neurocontrollers; permanent magnet motors; rotors; sensorless machine control; synchronous motor drives; velocity control; voltage measurement; cost reduction; current measurement; current prediction error; electrical motor model; mechanical motor model; network topology; neural network speed estimator; permanent magnet synchronous motor control; rotor speed estimation; sensorless PMSM control; speed drive; voltage measurement; Equations; Estimation; Jacobian matrices; Mathematical model; Neurons; Rotors; Training;
Conference_Titel :
Power Engineering, Energy and Electrical Drives (POWERENG), 2011 International Conference on
Conference_Location :
Malaga
Print_ISBN :
978-1-4244-9845-1
Electronic_ISBN :
2155-5516
DOI :
10.1109/PowerEng.2011.6036447