Design and Digital Implementation of Controller for PMSM Using Extended Kalman Filter

Abstract

A novel digital implementation of speed controller for a Permanent Magnet Synchronous Motor (PMSM) with disturbance rejection using conventional observer combined with Extended Kalman Filter (EKF) is proposed. First, the EKF is constructed to achieve a precise estimation of the speed and current from the noisy measurement. Second, a proportional integral derivative (PID) controller is developed based on Linear Quadratic Regulator (LQR) to achieve speed command tracking performance. Then, an observer is designed and its error is utilized to provide load disturbance compensation. The proposed method greatly enhances the PMSM performance by reducing the control signal variation as well as the disturbance. The speed control performance is significantly improved compared to the case when we have an observer acting alone. The simulation results for the speed response and variation of the states when the PMSM is subjected to the load disturbance are presented. The results verify the effectiveness of the proposed method.

Optimisation of Torque Ripples in Permanent Magnet Synchronous Motor using Hysteresis Current Controller

“…have seven membership functions, each with limits as E (-100 to +100) and C.E. (-1e 6 to +1e 6 ). The Hysteresis controller is used for pulse width modulation signal generation purposes.…”

“…This reduction is advantageous since it improves the efficiency of the inverter circuit. It is also used as input of measured speed and three-phase stator currents for comparison in PMSM drive [6]. The major drawback of P.I.…”

Position and Speed Estimation of PMSM Based on Extended Kalman Filter Tuned by Biogeography-Based-Optimization

“…During the last few years, Extended Kalman Filter (EKF) was employed to estimate PMSM rotor speed and position considered as one of the best tools of state estimation using stator currents and voltages [5,19]. Therefore, the most important benefit of the EKF over is its capability of tracking non-linear system dynamics with higher accuracy, high dynamic performance, disturbance resistance and it can operate under stochastic uncertainties (model uncertainties and inherent nonlinearities).…”

Comparison of three estimators used in a sensorless MPPT strategy for a wind energy conversion chain based on a PMSG

“…The main objective of this paper is to compare three types of estimators used to build the sensorless MPPT. The first estimator is an Angle Tracking observer (ATO) [4], the second is the Extended Kalman Filter (EKF) [5] and the third is the Synchronous Reference Frame Phase Locked Loop (SRF-PLL) [6]. The global wind conversion chain is presented in Fig.1.…”