Constant switching frequency model predictive control for permanent magnet linear synchronous motor

Abstract

Aim: This paper proposes constant switching frequency model predictive control (CSF-MPC) for a permanent magnet linear synchronous motor (PMLSM) to improve the steady state and dynamic performance of the drive system.
 Methods: The conventional finite control set model predictive control (FCS-MPC) can be combined with a pulse width modulation (PWM) modulator due to an effective cost function optimization algorithm which is from the idea of dichotomy. In the algorithm, all the voltage vectors in the constrained vector plane are dynamically selected and calculated through iteration. The whole system including control algorithm and mathematical model of PMLSM is built and tested by simulation using MATLAB/Simulink. Besides, the control algorithm is tested in the FPGA controller through FPGA-in-the-Loop test.
 Results: With the modern digital processors or control hardware such as digital signal processors (DSPs) or field programmable gate arrays (FPGAs), the algorithm can be easily executed in less than 10-micro second. This is very proper for industrial applications. The proposed control algorithm is implemented on FPGA and tested by FPGA-in-the-Loop method. The proposed control algorithm can improve the performance of drive system greatly.
 Conclusion: The proposed CSF-MPC for PMLSM not only keeps the same dynamic transient performance as FCS-MPC but also greatly decreases the torque ripple in steady state. Furthermore, CSF-MPC is also robust to parameter variations. Simulation and FPGA-in-the-Loop results illustrate that CSF-MPC has an attractive performance for PMLSM drives.