scholarly journals Multi-Functional Model Predictive Control with Mutual Influence Elimination for Three-Phase AC/DC Converters in Energy Conversion

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1616 ◽  
Author(s):  
Xiaolong Shi ◽  
Jianguo Zhu ◽  
Dylan Lu ◽  
Li Li
Keyword(s):  
Steady State ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Mutual Influence ◽  
Dynamic State ◽  
Switching Frequency ◽  
Digital Implementation ◽  
Three Phase ◽  
One Step ◽  
Steady State Performance

Conventional model predictive control (MPC)-based direct power control of the three-phase full-bridge AC/DC converter usually suffers from the parametric coupling between active and reactive powers. A reference change of either the active or reactive power will influence the other, deteriorating the dynamic-state performance. In addition, the steady-state performance affected by one-step-delay arising from computation and communication processes in the digital implementation should be improved in consideration of switching frequency reduction. In combination with the proposed novel mutual influence elimination constraint, this paper proposes the multi-functional MPC for three-phase full-bridge AC/DC converters to improve both the steady and dynamic performances simultaneously. It has various advantages such as one-step-delay compensation, power ripple reduction, and switching frequency reduction for steady-state performance as well as mutual influence elimination for dynamic capability. The simulation and experimental results are obtained to verify the effectiveness of the proposed method.

scholarly journals Current Prediction-Based Three-Vector Voltage Optimization System for the Induction Motor with Current Static Error Correction

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Li Haixia ◽  
Lin Jican
Keyword(s):  
Steady State ◽  
Model Predictive Control ◽  
Induction Motor ◽  
Predictive Control ◽  
Control Method ◽  
Tracking Error ◽  
Current Control ◽  
Static Error ◽  
Control Stability ◽  
Steady State Performance

In the present study, the current control method of the model predictive control is applied to the field-oriented control induction motor. The augmentation model of the motor is initially established based on the stator current equation, which performs the current predictive control and formulates the new cost function by means of tracking error. Then, the influence of parameter error on the current control stability in the prediction model is analysed, and the current static error is corrected according to the correlation between the input and feedback. Finally, a simple and effective three-vector control strategy is proposed. Moreover, three adjacent basic voltage vectors are utilized, and then six candidate voltage vectors are synthesized in each sector to replace eight basic voltage vectors in the conventional model predictive control (MPC). The obtained results show that synthesized vectors, which have arbitrary amplitude and direction, significantly expand the coverage of the system’s control set, reduce the torque and flux pulsation in the conventional MPC, and improve the steady-state performance of the system. Finally, the dSPACE platform is employed to validate the performed experiment. It is concluded that the proposed method can reduce the torque and flux pulse, perform the induction motor current control, and improve the steady-state performance of the system.

scholarly journals An MPC Scheme with Enhanced Active Voltage Vector Region for V2G Inverter

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1312
Author(s):  
Lie Xia ◽  
Lianghui Xu ◽  
Qingbin Yang ◽  
Feng Yu ◽  
Shuangqing Zhang
Keyword(s):  
Steady State ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Harmonic Distortion ◽  
Sampling Period ◽  
Duty Ratio ◽  
Output Current ◽  
Vehicle To Grid ◽  
Voltage Vector ◽  
Steady State Performance

In this paper, a model predictive control (MPC) scheme with an enhanced active voltage vector region (AV2R) was developed and implemented to achieve better steady-state performance and lower total harmonic distortion (THD) of the output current for a vehicle-to-grid (V2G) inverter. Firstly, the existing MPC methods conducted with single vector and two vectors during one sampling period were analyzed and the corresponding AV2Rs were elaborated. Secondly, the proposed strategy was investigated, aiming at expanding the AV2R and improving the steady-state performance accordingly. A formal mathematical methodology was studied in terms of duty ratio calculation. Lastly, the proposed method was carried out through experimentation. For comparison, the experimental results of the three mentioned methods were provided as well, proving the effectiveness of the proposed algorithm.

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

2018 ◽  
Vol 4 (3 suppl. 1) ◽  
pp. 279-288 ◽  
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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