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Energies
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Advanced Control in Power Electronics, Drives and Generators
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Advanced Control in Power Electronics, Drives and Generators

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F3: Power Electronics".

Deadline for manuscript submissions: 17 June 2024 | Viewed by 4185

Special Issue Editors

Prof. Dr. Emmanuel Delaleau

E-Mail Website
Guest Editor
Institut de Recherche Dupuy de Lôme, UMR CNRS 6027, École Nationale d’Ingénieurs de Brest, 29200 Brest, France
Interests: control theory; control applications; mechatronics; differential flatness; model-free control; AUVs
Special Issues, Collections and Topics in MDPI journals
Dr. Jean-Matthieu Bourgeot

E-Mail Website
Guest Editor
Institut de Recherche Dupuy de Lôme, UMR CNRS 6027, École Nationale d’Ingénieurs de Brest, Plouzané, France
Interests: control theory; control applications; fault-tolerant control ; renewable energy technologies

Special Issue Information

Dear Colleagues,

Advanced Control has led to many breakthroughs in drives and generators technology, as well as in power electronics. These openings have arisen both in theory and in practice, including “vector control” of electrical machines and “direct torque control” of electrical motors. In the field of power electronics, the improvements of control lead to evolved converter topologies, such as multilevel converters, and to maximum power point tracking for renewable energy devices. One can also cite sensor-less controls, harmonic reduction and current ripple reduction as consequences of advanced control.

This Special Issue aims to collect original research or review articles on recent advancements in the field of control of drives, generators and power electronics, especially nonlinear control; control that is either reliant or non-reliant on a model; and flatness based-control. Topics of interest include (but are not limited to): topologies and control of power converters and motor drives; control and management of renewable energy systems; fault-tolerant control methods; predictive control of power converters; power-quality control in renewable energy systems; real-time control and simulations of power converters; modeling and model-based control of switch-mode power converters.

Prof. Dr. Emmanuel Delaleau
Dr. Jean-Matthieu Bourgeot
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • advanced control
  • nonlinear control
  • electrical motors
  • electrical drives
  • electrical generators
  • power electronics converters

Published Papers (6 papers)

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Research

19 pages, 2520 KiB  
Article
Sensorless Model Predictive Control of Permanent Magnet Synchronous Motors Using an Unscented Kalman Filter
by Dariusz Janiszewski
Energies 2024, 17(10), 2387; https://doi.org/10.3390/en17102387 - 16 May 2024
Viewed by 256
Abstract
This paper deals with the application of the Model Predictive Control (MPC) algorithm to the sensorless control of a Permanent Magnet Synchronous Motor (PMSM). The proposed estimation strategy, based on the unscented Kalman filter (UKF), uses only the measurement [...] Read more.
This paper deals with the application of the Model Predictive Control (MPC) algorithm to the sensorless control of a Permanent Magnet Synchronous Motor (PMSM). The proposed estimation strategy, based on the unscented Kalman filter (UKF), uses only the measurement of the motor current for the online estimation of speed, rotor position and load torque. Information about the system state is fed into the MPC algorithm. The results verify the effectiveness and applicability of the proposed sensorless control technique. To demonstrate its real-world applicability, implementation in low-speed direct drive astronomy telescope mount systems is investigated. The outcomes of the implementation are thoroughly examined, leading to insightful conclusions drawn from the observed results. Through rigorous theoretical analysis and extensive simulation studies, this paper establishes a solid foundation for the proposed sensorless control technique. The results obtained from simulation studies and real-world applications underscore the efficacy and versatility of the proposed approach, offering valuable insights for the advancement of sensorless control strategies in motor applications. The main aim of this work is to demonstrate and validate the practical feasibility of combining two complex techniques, establishing that such an integration is not only possible but also effective in achieving the desired objectives. Full article
(This article belongs to the Special Issue Advanced Control in Power Electronics, Drives and Generators)
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19 pages, 10817 KiB  
Article
Common-Mode Voltage Reduction Method Based on Variable Sampling Frequency Finite Control Set-Model Predictive Control for PMSM Drive Systems
by Yoon-Seong Lee, Kyoung-Min Choo, Chang-Hee Lee, Chang-Gyun An, Junsin Yi and Chung-Yuen Won
Energies 2024, 17(6), 1443; https://doi.org/10.3390/en17061443 - 17 Mar 2024
Cited by 1 | Viewed by 587
Abstract
In this article, a finite control set-model predictive control (FCS-MPC) with variable sampling time is proposed. A zero-voltage vector appears in the dead time between specific voltage vectors, resulting in an unintentionally large common-mode voltage. Herein, a large common-mode voltage was suppressed, and [...] Read more.
In this article, a finite control set-model predictive control (FCS-MPC) with variable sampling time is proposed. A zero-voltage vector appears in the dead time between specific voltage vectors, resulting in an unintentionally large common-mode voltage. Herein, a large common-mode voltage was suppressed, and the load current was controlled using a voltage vector combination that did not cause a zero-voltage vector in dead time. Additionally, to improve the total harmonic distortion (THD) of the load current, the intersection of the predicted current and the command current by all the volage vectors (VVs) in the combination is confirmed. The VV where the intersection occurs is selected as the optimal VV. This optimal VV is applied to the point where the predicted current and the reference current intersect. The applicable range of the sampling time should be selected by considering the calculation time and number of switching. Through the proposed FCS-MPC strategy, not only can the common-mode voltage be limited to within ±Vdc/6, but an improved THD can also be obtained compared to the existing method using fixed sampling. The proposed method was verified through PSIM simulation and experimental results. Full article
(This article belongs to the Special Issue Advanced Control in Power Electronics, Drives and Generators)
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18 pages, 10066 KiB  
Article
A Comprehensive Review on Comparison and Performance of Five-Phase Space Vector Pulse Width Modulation Overmodulation Strategies
by Tiankui Sun, Yingying Sun, Beijia Ma, Feifei Bu, Ya Qin, Qi Liu and Sorin Ioan Deaconu
Energies 2024, 17(6), 1356; https://doi.org/10.3390/en17061356 - 12 Mar 2024
Viewed by 529
Abstract
High-performance overmodulation strategies for voltage source inverters (VSIs) can further broaden the operation range of machines. Among them, Space Vector Pulse Width Modulation (SVPWM) is worth researching as it performs well in digital implementation. This paper presents a detailed comparison of various SVPWM [...] Read more.
High-performance overmodulation strategies for voltage source inverters (VSIs) can further broaden the operation range of machines. Among them, Space Vector Pulse Width Modulation (SVPWM) is worth researching as it performs well in digital implementation. This paper presents a detailed comparison of various SVPWM overmodulation strategies and analysis of their performance. It firstly briefly elaborates fundamental laws of two subspaces of five-phase VSIs. Then, it focuses on several overmodulation strategies. Their corresponding basic principles and main characteristics are researched, and conclusions are given. In addition, differences and relationships between them are proved and summarized. Lastly, comparative simulations and experiments were carried out and verify that in the overmodulation region, the output voltage distortion degree increases with the increase in modulation ratio, and strategies with more control degrees of freedom (CDFs) are capable of better controlling the third harmonic subspace, which means that higher-quality output voltage waveforms would be obtained. Full article
(This article belongs to the Special Issue Advanced Control in Power Electronics, Drives and Generators)
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25 pages, 5044 KiB  
Article
Induction Motor Improved Vector Control Using Predictive and Model-Free Algorithms Together with Homotopy-Based Feedback Linearization
by Madalin Costin and Corneliu Lazar
Energies 2024, 17(4), 875; https://doi.org/10.3390/en17040875 - 14 Feb 2024
Viewed by 556
Abstract
Vector control of an induction machine (IM) is typically performed by using cascade control structures with conventional linear proportional–integral (PI) controllers, the inner loop being designed for current control and the outer loop for rotor flux and speed control. In this paper, starting [...] Read more.
Vector control of an induction machine (IM) is typically performed by using cascade control structures with conventional linear proportional–integral (PI) controllers, the inner loop being designed for current control and the outer loop for rotor flux and speed control. In this paper, starting with the dq model of the IM, advanced control algorithms are proposed for the two control loops of the cascade structure. For the current inner loop, after the decoupling of the two dq currents, predictive control algorithms are employed to independently control the currents, considering the constraints imposed by the electrical signal physics limitations. Since the outer loop has a nonlinear affine multivariable plant model, a homotopy-based variant of feedback linearization is used to obtain a nonsingular decoupling matrix of the feedback transformation even when the rotor flux is zero at the start-up of the motor. During the continuous variation in the homotopy parameter, the plant model is variable and, for this reason, model-free algorithms are used to control the flux and speed of the IM due to their capabilities to manage complex dynamics from data without requiring knowledge of the plant model. The performances of the proposed cascade control strategy with advanced algorithms in the two loops were tested by simulation and compared with those obtained with conventional PI controllers, resulting in better dynamic behavior for predictive and model-free control. Full article
(This article belongs to the Special Issue Advanced Control in Power Electronics, Drives and Generators)
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17 pages, 12564 KiB  
Article
Robust Predictive Current Control of PMSG Wind Turbines with Sensor Noise Suppression
by Junda Li, Oluleke Babayomi, Zhenbin Zhang and Zhen Li
Energies 2023, 16(17), 6255; https://doi.org/10.3390/en16176255 - 28 Aug 2023
Viewed by 798
Abstract
Model predictive control (MPC) is an efficient and multi-functional control scheme for synchronous permanent magnet generators (PMSGs). However, the effective management of traditional MPC depends on precise system models. Multiple uncertainties of permanent magnet flux, motor inductance, filter inductance and parameter measurement noise [...] Read more.
Model predictive control (MPC) is an efficient and multi-functional control scheme for synchronous permanent magnet generators (PMSGs). However, the effective management of traditional MPC depends on precise system models. Multiple uncertainties of permanent magnet flux, motor inductance, filter inductance and parameter measurement noise will limit MPC’s performance. The conventional linear extended state observer (ESO) can perform robust predictive control of the ultralocal model of the PMSG system to cope with parameter mismatches. However, the ESO is limited in balancing disturbance rejection with measurement noise attenuation. Since the amplification of high-frequency noise pollution can lead to both poor control performance and system instability, this challenge is of significant importance. To solve the problem, a new hybrid parallel cascaded ESO (PCESO) model-free predictive control framework is proposed using the three-level neutral-point-clamped (NPC) power electronic converter, on both the machine side and grid side. Analytical discussions of the time and frequency domain characteristics of the PCESO demonstrate its superior characteristics over the ESO. The proposed method can effectively balance parameter mismatch, disturbance rejection and high-frequency noise suppression. Finally, the effectiveness of the proposed method, under uncertainties of parameter mismatches, measurement noise and permanent magnet flux, is verified through real-time hardware-in-the-loop tests on a back-to-back grid-tied PMSG interfaced with an NPC power converter. Full article
(This article belongs to the Special Issue Advanced Control in Power Electronics, Drives and Generators)
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17 pages, 2389 KiB  
Article
Comparative Study of Passivity, Model Predictive, and Passivity-Based Model Predictive Controllers in Uninterruptible Power Supply Applications
by Shafquat Hussain, Abualkasim Bakeer, Ihab S. Mohamed, Mario Marchesoni and Luis Vaccaro
Energies 2023, 16(15), 5594; https://doi.org/10.3390/en16155594 - 25 Jul 2023
Viewed by 749
Abstract
Voltage source converters are widely used in distributed generation (DG) and uninterruptible power supply (UPS) applications. This paper aims to find the controller that performs best when model changes occur in the system, showing insensitivity to parameter variations. A comparison of the finite [...] Read more.
Voltage source converters are widely used in distributed generation (DG) and uninterruptible power supply (UPS) applications. This paper aims to find the controller that performs best when model changes occur in the system, showing insensitivity to parameter variations. A comparison of the finite control set model predictive controller (FCS-MPC), interconnection and damping assignment passivity-based controller (IDA-PBC), and passivity-based model predictive control (PB-MPC) reveals that the PB-MPC provides high resistance to these unexpected LC filter changes in the converter. The second aim of the paper is to reduce the total harmonic distortion (THD) of the output voltage of the three-phase voltage source inverter (VSI). A high total harmonic distortion (THD) value exists in the voltage waveform of the three-phase voltage source inverter (VSI), feeding a non-linear load. A MATLAB simulation was performed using three control techniques for a three-phase VSI feeding: linear load, unbalanced load, and non-linear load. The PB-MPC performs better than the FCS-MPC and IDA-PBC in terms of having a low THD value in the output voltage of the converter under all types of applied loads, improving the THD by up to 30%, and having low variation in THD with mismatched filter parameters, as shown in the bar charts in the results section. Overall, the PB-MPC controller improves the robustness under parameter mismatch and reduces the computational burden. PB-MPC reduces the THD value because it integrates power shaping and the injection of damping resistances into the VSI. Full article
(This article belongs to the Special Issue Advanced Control in Power Electronics, Drives and Generators)
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