Abstract
In this paper, a simplified efficient method for sensorless finite set current predictive control (FSCPC) for synchronous reluctance motor (SynRM) based on extended Kalman filter (EKF) is proposed. The proposed FSCPC is based on reducing the computation burden of the conventional FSCPC by using the commanded reference currents to directly calculate the reference voltage vector (RVV). Therefore, the cost function is calculated for only three times and the necessity to test all possible voltage vectors will be avoided. For sensorless control, EKF is composed to estimate the position and speed of the rotor. Whereas the performance of the proposed FSCPC essentially necessitates the full knowledge of SynRM parameters and provides an insufficient response under the parameter mismatch between the controller and the motor, online parameter estimation based on EKF is combined in the proposed control strategy to estimate all parameters of the machine. Furthermore, for simplicity, the parameters of PI speed controller and initial values of EKF covariance matrices are tuned offline using Particle Swarm Optimization (PSO). To demonstrate the feasibility of the proposed control, it is implemented in MATLAB/Simulink and tested under different operating conditions. Simulation results show high robustness and reliability of the proposed drive.
Highlights
Simple designed and rugged synchronous reluctance motors (SynRMs) have received more attention because they have low cost, high density, and Less complex control, in contrast to the induction motor [1,2]
In (22), the parameters of the SynRM ( Rs, Ld, and Lq ) are online estimated by the extended Kalman filter (EKF), which improve the robustness of the proposed finite set current predictive control (FSCPC) against variations of the machine parameters (i.e., if the parameters vary, the EKF will detect the new values of the parameters and update them in (22))
The observation performances of presented EKF are compared with the nominal values of the SynRM for a wide speed range including the low and reversal speed
Summary
Simple designed and rugged synchronous reluctance motors (SynRMs) have received more attention because they have low cost, high density, and Less complex control, in contrast to the induction motor [1,2]. To implement the proposed control method, the position and speed of the rotor and the measured currents should be fed back to the predictive model. This is achieved by a mechanical encoder and sensor currents. In low-cost applications, the position accuracy usually is an insignificant concern These previous reasons have been encouraged the researchers to propose sensorless control of electrical drives. In [34], the sensorless predictive control of synchronous reluctance motor based on high-frequency injection is presented. Sensorless and computationally-efficient current predictive control of synchronous reluctance motor based on extended Kalman filter is proposed.
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