Experimental Design of Fixed Switching Frequency Model Predictive Control for Sensorless Five-Level Packed U-Cell Inverter

Several control strategies have been proposed with the aim to get a desired behavior in the power converter variables. The most employed control techniques are linear control, nonlinear control based on linear and nonlinear feedback, and predictive control. The controllers associated with linear and nonlinear algorithms usually have a fixed switching frequency, featuring a defined spectrum given by the pulse width modulation (PWM) or space vector modulation (SVM) time period. On the other hand, finite set model predictive control (FS-MPC) is known to present a variable switching frequency that results too high for high power applications, increasing losses, reducing the switches lifetime and, therefore, limiting its application. This paper proposes a predictive control approach using a very low sampling frequency, allowing the use of predictive control in high power applications. The proposed method is straightforward to understand, is simple to implement, and can be computed with off-the-shelf digital systems. The main advantage of the proposed control algorithm comes from the combination of the model predictive control and the SVM technique, drawing the principal benefits of both methods. The provided experimental results are satisfactory, displaying the nature of space vector-based schemes but at the same time the fast response as expected in predictive control.

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

Transportation systems and technology ◽

10.17816/transsyst201843s1279-288 ◽

2018 ◽

Vol 4 (3 suppl. 1) ◽

pp. 279-288 ◽

Cited By ~ 1

Author(s):

Zhixun Ma ◽

Yuanzhe Zhao ◽

Yan Sun ◽

Zhiming Liao ◽

Guobin Lin

Keyword(s):

Steady State ◽

Model Predictive Control ◽

Permanent Magnet ◽

Predictive Control ◽

Control Algorithm ◽

Synchronous Motor ◽

Drive System ◽

Switching Frequency ◽

Frequency Model ◽

Linear Synchronous Motor

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.

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