scholarly journals Multi-Virtual-Vector Model Predictive Current Control for Dual Three-Phase PMSM

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7292
Author(s):  
Tianjiao Luan ◽  
Zhichao Wang ◽  
Yang Long ◽  
Zhen Zhang ◽  
Qi Li ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Current Control ◽  
Vector Model ◽  
Permanent Magnet Synchronous Machine ◽  
Control Performance ◽  
Voltage Vector ◽  
Three Phase ◽  
Tracking Ability ◽  
Zero Vector

This paper proposes a multi-virtual-vector model predictive control (MPC) for a dual three-phase permanent magnet synchronous machine (DTP-PMSM), which aims to regulate the currents in both fundamental and harmonic subspace. Apart from the fundamental α-β subspace, the harmonic subspace termed x-y is decoupled in multiphase PMSM according to vector space decomposition (VSD). Hence, the regulation of x-y currents is of paramount importance to improve control performance. In order to take into account both fundamental and harmonic subspaces, this paper presents a multi-virtual-vector model predictive control (MVV-MPC) scheme to significantly improve the steady performance without affecting the dynamic response. In this way, virtual vectors are pre-synthesized to eliminate the components in the x-y subspace and then a vector with adjustable phase and amplitude is composed of two effective virtual vectors and a zero vector. As a result, an enhanced current tracking ability is acquired due to the expanded output range of the voltage vector. Lastly, both simulation and experimental results are given to confirm the feasibility of the proposed MVV-MPC for DTP-PMSM.

scholarly journals Model predictive control of multilevel cascaded converter with boosting capability – experimental results

2017 ◽  
Vol 65 (5) ◽  
pp. 589-599
Author(s):  
P. Wiatr ◽  
A. Kryński
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Output Voltage ◽  
Current Control ◽  
Experimental Results ◽  
Laboratory Model ◽  
Modular Construction ◽  
Three Phase ◽  
Cascaded Converter ◽  
Level Converter

Abstract The main goal of this paper is to present a five-level converter with the feature of output voltage boosting capability. Thanks to its modular construction and single DC source usage, 5LCHB converter becomes an important alternative for two-level converters operating with DC-DC converters that use bulky inductors. Furthermore, model predictive control (MPC) method is presented, which allows for boosting output voltage of presented converter while providing three-phase load current control and flying capacitor voltage stabilization. The last section describes a 5kVA laboratory model of five-level hybrid converter interfacing RL load and shows experimental results confirming theoretical analysis derived in previous sections.

scholarly journals Multiple-Vector Model Predictive Control with Fuzzy Logic for PMSM Electric Drive Systems

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1727
Author(s):  
Ibrahim Farouk Bouguenna ◽  
Ahmed Tahour ◽  
Ralph Kennel ◽  
Mohamed Abdelrahem
Keyword(s):  
Fuzzy Logic ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Electric Drive ◽  
Fuzzy Logic Controller ◽  
Sampling Period ◽  
Vector Model ◽  
Voltage Vector ◽  
Drive Systems ◽  
Sampling Instant

This article presents a multiple-vector finite-control-set model predictive control (MV-FCS-MPC) scheme with fuzzy logic for permanent-magnet synchronous motors (PMSMs) used in electric drive systems. The proposed technique is based on discrete space vector modulation (DSVM). The converter’s real voltage vectors are utilized along with new virtual voltage vectors to form switching sequences for each sampling period in order to improve the steady-state performance. Furthermore, to obtain the reference voltage vector (VV) directly from the reference current and to reduce the calculation load of the proposed MV-FCS-MPC technique, a deadbeat function (DB) is added. Subsequently, the best real or virtual voltage vector to be applied in the next sampling instant is selected based on a certain cost function. Moreover, a fuzzy logic controller is employed in the outer loop for controlling the speed of the rotor. Accordingly, the dynamic response of the speed is improved and the difficulty of the proportional-integral (PI) controller tuning is avoided. The response of the suggested technique is verified by simulation results and compared with that of the conventional FCS-MPC.

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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