Sensorless control for permanent magnet synchronous motor using a neural network based adaptive estimator

Chung-Jin Kwon; Sung-Joong Kim; Woo-Young Han; Won-Kyoung Min

doi:10.1117/12.664658

2 May 2006 Sensorless control for permanent magnet synchronous motor using a neural network based adaptive estimator

Chung-Jin Kwon, Sung-Joong Kim, Woo-Young Han, Won-Kyoung Min

Proceedings Volume 6042, ICMIT 2005: Control Systems and Robotics; 60422F (2006) https://doi.org/10.1117/12.664658
Event: ICMIT 2005: Merchatronics, MEMS, and Smart Materials, 2005, Chongqing, China

Abstract

The rotor position and speed estimation of permanent-magnet synchronous motor(PMSM) was dealt with. By measuring the phase voltages and currents of the PMSM drive, two diagonally recurrent neural network(DRNN) based observers, a neural current observer and a neural velocity observer were developed. DRNN which has self-feedback of the hidden neurons ensures that the outputs of DRNN contain the whole past information of the system even if the inputs of DRNN are only the present states and inputs of the system. Thus the structure of DRNN may be simpler than that of feedforward and fully recurrent neural networks. If the backpropagation method was used for the training of the DRNN the problem of slow convergence arise. In order to reduce this problem, recursive prediction error(RPE) based learning method for the DRNN was presented. The simulation results show that the proposed approach gives a good estimation of rotor speed and position, and RPE based training has requires a shorter computation time compared to backpropagation based training.

Citation Download Citation

Chung-Jin Kwon, Sung-Joong Kim, Woo-Young Han, and Won-Kyoung Min "Sensorless control for permanent magnet synchronous motor using a neural network based adaptive estimator", Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 60422F (2 May 2006); https://doi.org/10.1117/12.664658

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KEYWORDS

Neural networks

Sensors

Neurons

Magnetic sensors

Computer simulations

Data hiding

Electronics engineering

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