A New Modulated Finite Control Set-Model Predictive Control of Quasi-Z-Source Inverter for PMSM Drives

In this paper, a new modulated finite control set-model predictive control (FCS-MPC) methodology is proposed for a quasi-Z-source inverter (qZSI). The application of the qZSI in this paper is to drive the permanent magnet synchronous machine (PMSM). The proposed methodology calculates the optimal duration time (ODT) for the candidate vector from the switching patterns of the inverter after it is selected from the FCS-MPC algorithm. The control objective of the FCS-MPC are the three-phase currents of PMSM, when the motor speed is below or equal to the base speed. While at a speed beyond the based speed, the inductor current and capacitor voltage of the qZS network are added as control objectives. For each candidate optimal vector, the optimal time, which is a part of the sampling interval, is determined based on minimizing the ripples of the control objectives using a quadratic cost function. Then, the optimal vector is applied only to the inverter switches during the calculated ODT at the start of the sampling interval, while the zero vector is applied during the remaining part of the sampling interval. To reduce the calculation burden, the zero-state is excluded from the possible states of the inverter, and the sub-cost function definition is used for the inductor current regulation. The proposed modulated FCS-MPC is compared with the unmodulated FCS-MPC at the same parameters to handle a fair comparison. The simulation results based on the MATLAB/Simulink© software shows the superiority of the proposed algorithm compared to the unmodulated FCS-MPC in terms of a lower ripple in the inductor current and capacitor voltage, and a lower THD for the PMSM currents.

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Finite control set model predictive control to balance DC-link capacitor voltage for TType NPC inverter of grid-connected photovoltaic systems

Science and Technology Development Journal ◽

10.32508/stdj.v18i3.880 ◽

2015 ◽

Vol 18 (3) ◽

pp. 5-17

Author(s):

Dzung Quoc Phan ◽

Tuyen Dinh Nguyen ◽

Nhat Minh Nguyen

Keyword(s):

Model Predictive Control ◽

Cost Function ◽

Predictive Control ◽

Switching Frequency ◽

Photovoltaic Systems ◽

Delay Compensation ◽

Capacitor Voltage ◽

Finite Control ◽

Control Set ◽

The Cost

This paper proposes the Finite control set Model Predictive Control (FCS-MPC) with delay compensation for three-phase threelevel T-Type NPC inverter (T-Type NPC) of grid-connected photovoltaic systems (PV). The proposed FCS-MPC controls the objectives: current tracking control, DC-link capacitor voltage balance, the reduction of switching frequency to ensure issues of the power quality and improve the efficiency of grid-connected of PV system. The cost function of the proposed FCS-MPC uses the 27 possible switching states generated by TType NPC, the optimal switching state is selected in each sampling time that minimizes the cost function. The proposed FCS-MPC has also proposed the delay compensation with two-step prediction horizon at time k+2 to reduce the total harmonic distortion (THD) of the grid current. The proposed FCS-MPC is verified by using Matlab/Simulink.

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Total Harmonic Distortion Oriented Finite Control Set Model Predictive Control for Single-Phase Inverters

Energies ◽

10.3390/en11123467 ◽

2018 ◽

Vol 11 (12) ◽

pp. 3467 ◽

Cited By ~ 4

Author(s):

Po Li ◽

Ruiyu Li ◽

Haifeng Feng

Keyword(s):

Model Predictive Control ◽

Cost Function ◽

Predictive Control ◽

Single Phase ◽

Tracking Error ◽

Harmonic Distortion ◽

Total Harmonic Distortion ◽

Finite Control ◽

Control Set ◽

The Cost

Inverters are commonly controlled to generate AC current and Total Harmonic Distortion (THD) is the core index in judging the control effect. In this paper, a THD oriented Finite Control Set Model Predictive Control (FCS MPC) scheme is proposed for the single-phase inverter, where a optimization problem is solved to obtain the switching law for realization. Different from the traditional cost function, which focuses on the instantaneous deviation of amplitude between predictive current and its reference, we redesign a cost function that is the linear combination of the current fundamental tracking error, instantaneous THD value and DC component in one fundamental cycle (for 50 Hz, it is 0.02 s). Iterative method is developed for rapid calculation of this cost function. By choosing a switching state from a FCS to minimize the cost function, a FCS MPC is finally constructed. Simulation results in Matlab/Simulink and experimental results on rapid control prototype platform show the effect of this method. Analyses illustrate that, by choosing suitable weight of the cost function, the performance of this THD oriented FCS MPC method is better than the traditional one.

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Direct Torque Control of PMSM with Modified Finite Set Model Predictive Control

Energies ◽

10.3390/en13010234 ◽

2020 ◽

Vol 13 (1) ◽

pp. 234 ◽

Cited By ~ 5

Author(s):

GuangQing Bao ◽

WuGang Qi ◽

Ting He

Keyword(s):

Model Predictive Control ◽

Cost Function ◽

Predictive Control ◽

Direct Torque Control ◽

Torque Ripple ◽

Torque Control ◽

Voltage Vector ◽

Finite Control ◽

Finite Set ◽

Control Set

A direct torque control (DTC) with a modified finite set model predictive strategy is proposed in this paper. The eight voltage space vectors of two-level inverters are taken as the finite control set and applied to the model predictive direct torque control of a permanent magnet synchronous motor (PMSM). The duty cycle of each voltage vector in the finite set can be estimated by a cost function, which is designed based on factors including the torque error, maximum torque per ampere (MTPA), and stator current constraints. Lyapunov control theory is introduced in the determination of the weight coefficients of the cost function to guarantee stability, and thus the optimal voltage vector reference value of the inverter is obtained. Compared with the conventional finite control set model predictive control (FCS-MPC) method, the torque ripple is reduced and the robustness of the system is clearly improved. Finally, the simulation and experimental results verify the effectiveness of the proposed control scheme.

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Real-Time Implementation of an Optimized Model Predictive Control for a 9-Level CSC Inverter in Grid-Connected Mode

Sustainability ◽

10.3390/su13158119 ◽

2021 ◽

Vol 13 (15) ◽

pp. 8119

Author(s):

Alamera Nouran Alquennah ◽

Mohamed Trabelsi ◽

Khaled Rayane ◽

Hani Vahedi ◽

Haitham Abu-Rub

Keyword(s):

Model Predictive Control ◽

Real Time ◽

Predictive Control ◽

Reference Values ◽

Unity Power Factor ◽

Capacitor Voltage ◽

Finite Control ◽

Optimized Model ◽

Sinusoidal Current ◽

Control Set

The Crossover Switches Cell (CSC) is a recent Single DC-Source Multilevel Inverter (SDCS-MLI) topology with boosting abilities. In grid-connected PV applications, the CSC should be controlled to inject a sinusoidal current to the grid with low THD% and unity power factor, while balancing the capacitor voltage around its reference. These two objectives can be met through the application of a finite control set model predictive control (FCS-MPC) method. Thus, this paper proposes a design of an optimized FCS-MPC for a 9-level grid-tied CSC inverter. The switching actions are optimized using the redundant switching states. The design is verified through simulations and real-time implementation. The presented results show that the THD% of the grid current is 1.73%, and the capacitor voltage is maintained around its reference with less than 0.5 V mean error. To test the reliability of the control design, different scenarios were applied, including variations in the control reference values as well as the AC grid voltage. The presented results prove the good performance of the designed controller in tracking the reference values and minimizing the steady-state errors.

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