Sensorless speed control of permanent magnet synchronous motors by neural network algorithm

Abstract

The sliding mode control has the merits with respect to the variation of the disturbance and robustness. In this paper, the sensorless sliding-mode observer with least mean squared error approach for permanent magnet synchronous motor (PMSM) to detect the rotor position by counter electromotive force and then compute motor speed is designed and implemented. In addition, the neural network control is also used to compensate the PI gain tuning to increase the speed accuracy without regarding the errors of the current measurement and motor noise. In this paper, a digital signal processor TMS320F2812 utilizes its high-speed ADC module to get current feedback information and thus to estimate the rotor position and takes advantage of the built-in modules to achieve SVPWM current control so that the senseless speed control will be accomplished. The correctness and effectiveness of the proposed control system will be verified from the experimental results.