A Double-Voltage Vector Based Model Predictive Control Method for Three Phase Four-Switch Fault-Tolerant Converter

2019 ◽  
Author(s):  
Leilei Guo ◽  
Kaixuan Zhang ◽  
Lingzhi Cao ◽  
Linwang Dai ◽  
Nan Jin ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Fault Tolerant ◽  
Voltage Vector ◽  
Three Phase

scholarly journals A finite set-model predictive control based on FPGA flatform for eleven-level cascaded H-Bridge inverter fed induction motor drive

2021 ◽  
Vol 12 (2) ◽  
pp. 845
Author(s):  
Mai Van Chung ◽  
Do Tuan Anh ◽  
Phuong Vu
Keyword(s):  
Model Predictive Control ◽  
Induction Motor ◽  
Predictive Control ◽  
Control Method ◽  
Dynamic Responses ◽  
Delay Compensation ◽  
Voltage Vector ◽  
Finite Control ◽  
Finite Set ◽  
The Cost

Model predictive control has been considered as a powerful alternative control method in power converters and electrical drives recently. This paper proposes a novel method for finite control set predictive control algorithm foran induction motor fed by 11-level cascaded H-Bridge converter. To deal with the high computation volume of MPC algorithm applied for CHBconverter, 7-adjacent vectors method is applied for calculating the desired voltage vector which minimizes the cost function. Moreover, by utilizingfield programmable gate array (FPGA) platform with its flexible structure,the total execution time reduces considerably so that the selected voltage vector can be applied immediately without delay compensation. This method improves the dynamic responses and steady-state performance of the system. Finally, experimental results verify the effectiveness of control design

Model predictive control method with common-mode voltage suppression for dual three-phase permanent magnet synchronous motor

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1453-1460
Author(s):  
Zhifeng Zhang ◽  
Yue Wu ◽  
Sicong Ye
Keyword(s):  
Computational Complexity ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Common Mode ◽  
Current Harmonics ◽  
Common Mode Voltage ◽  
Three Phase

Recently, the interest in model predictive control (MPC) and dual three-phase drives has been growing rapidly. Due to the high redundancy of voltage vector in the system composed of dual three-phase permanent magnetic synchronous motor (PMSM) and six-phase inverter, the computational complexity and current harmonics of MPC are high. In addition, the zero vector has been used by traditional MPC, which will cause higher common-mode voltage. In this paper, a novel MPC method with twice predictions and synthetic vectors is proposed which can not only suppress common-mode voltage, but also reduce computational complexity and current harmonics. The mathematical model of a dual three-phase PMSM are verified by the experimental results under the common-mode voltage suppression.

scholarly journals A Novel Adaptive Model Predictive Control Based Three-Phase Inverter Current Control Method

2019 ◽  
Vol 9 (24) ◽  
pp. 5413 ◽  
Author(s):  
Mingyu Lei ◽  
Ying Zhang ◽  
Lexuan Meng ◽  
Yibo Wang ◽  
Zilong Yang ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Dynamic Performance ◽  
Current Control ◽  
Three Phase ◽  
Modification Method ◽  
Adaptive Model Predictive Control ◽  
Three Phase Inverter ◽  
Control Accuracy

This paper proposes a novel current control method based on Model Predictive Control (MPC) for three-phase inverters. The proposed method is based on an Adaptive MPC (A-MPC) with a PWM modulation. An innovative model parameter estimation and modification method is also proposed, leading to enhanced control accuracy. Comparing with traditional current control methods, such as PI and PR control, the proposed method has better dynamic performance. The transient dynamics, i.e., recovery time and overshoot, have been considerably improved. Simulation and experimental results are presented to validate the effectiveness of the proposal.

scholarly journals Three-Vector-Based Low Complexity Model Predictive Control for Soft Open Point

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Zhengqi Wang ◽  
Haoyu Zhou ◽  
Qunhai Huo ◽  
Sipeng Hao
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Low Complexity ◽  
Sampling Time ◽  
Vector Model ◽  
Dynamic State ◽  
Network Systems ◽  
Voltage Vector ◽  
Open Point

Soft open point (SOP) can improve the flexibility and reliability of power supplies; thus, they are widely used in distribution network systems. Traditional single-vector model predictive control (SV-MPC) can quickly and flexibly control the power and current at both ports of the SOP. However, SV-MPC can only select one voltage vector in a sampling time, producing large current ripples, and power fluctuations. In order to solve the above problems, this paper proposes a three-vector-based low complexity model predictive control (TV-MPC). In the proposed control method, two effective voltage vectors and one zero voltage vector are selected in a sampling time. For the two-port SOP, methods are given to judge the sectors on both sides and select the voltage vectors. Furthermore, the calculation method of the distribution time is proposed as well. Finally, the effectiveness of the proposed method is verified by steady-state and dynamic-state simulation results compared with the SV-MPC.

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