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Symmetry
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Symmetry/Asymmetry in Motor Control, Drives and Power Electronics
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Symmetry/Asymmetry in Motor Control, Drives and Power Electronics

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 8974

Special Issue Editors

Prof. Dr. Mingyi Wang

E-Mail Website
Guest Editor
School of Electrical Engineering and Automation, Harbin Institute of Technology, Herbin 150001, China
Interests: special electromagnetic device; control and drive of linear motors; linear electromagnetic launch; accumulation of electric energy; superconducting motors
Special Issues, Collections and Topics in MDPI journals
Dr. Qiang Tan

E-Mail Website
Guest Editor
School of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Interests: motor; maglev; electronics

Special Issue Information

Dear Colleagues,

The electromagnetic and mechanical structures of motors have typical symmetry characteristics; therefore, motors are widely used in industrial manufacturing, rail transit, military defense, electric power equipment, and other fields. Motor control drives the advancement of technology and has become a hot direction in research.

This issue mainly focuses on motor control, drives, and power electronics, including the latest research progress and achievements in power electronics and power transmission technology, motor system design, advanced drive control technology, magnetic levitation technology, position detection technology, parameter identification technology, and so on. We welcome scholars in the related fields to contribute their latest research results to our Special Issue.

Topics of research include, but are not limited to, the following:

  • Motor control and motor drives;
  • Motion control and servo systems;
  • Automotive power electronics;
  • Power converters;
  • Reliability, diagnostics and tolerance;
  • Magnetic levitation technology;
  • Parameter identification technology.

Prof. Dr. Mingyi Wang
Dr. Qiang Tan
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 250 words) can be sent to the Editorial Office for assessment.

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. Symmetry is an international peer-reviewed open access monthly 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 2400 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

  • motor
  • control
  • drive
  • power electronics
  • magnetic levitation
  • position detection
  • parameter identification

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Published Papers (4 papers)

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Research

18 pages, 2257 KB  
Article
Improved ADRC with Real-Time Disturbance Compensation for Gantry Synchronization over EtherCAT
by Gaochao Tan, Shu Wang and Qihong Zhou
Symmetry 2026, 18(3), 466; https://doi.org/10.3390/sym18030466 - 9 Mar 2026
Viewed by 446
Abstract
Dual linear motor-driven systems (DLMDS) are widely used in industrial manufacturing due to their high dynamic stability and robust performance, typically featuring a symmetric Y1–Y2 axis structure. High-precision synchronization control of the motion platform is crucial for overall system performance. However, in practice, [...] Read more.
Dual linear motor-driven systems (DLMDS) are widely used in industrial manufacturing due to their high dynamic stability and robust performance, typically featuring a symmetric Y1–Y2 axis structure. High-precision synchronization control of the motion platform is crucial for overall system performance. However, in practice, such systems are inevitably affected by mechanical installation errors, load disturbances, and nonlinear friction, which lead to the asymmetry of the Y1–Y2, severely degrading the synchronization accuracy between the two symmetric axes. To address these challenges, this paper proposes an EtherCAT-enabled active disturbance rejection control (ADRC) strategy for high-performance gantry synchronization systems. To cope with strong coupling effects, external disturbances, and high-speed operation, a master–slave synchronization architecture is developed based on ADRC and the EtherCAT cyclic synchronous torque (CST) mode. An extended state observer (ESO) is employed to estimate and compensate for lumped disturbances in real time, enabling precise synchronization without relying on an accurate mechanical model. Experimental results under both low-speed and high-speed operating conditions show that the proposed method significantly improves the synchronization stability and robustness compared with conventional cross-coupling control and master–slave control strategies. Specifically, the ADRC-based approach reduces synchronization errors by more than 20% under disturbance-free conditions and suppresses approximately 80% of disturbance-induced errors during high-speed operation. These results confirm the effectiveness and practical applicability of the proposed control strategy for high-precision gantry motion systems. Unlike conventional torque-mode implementations that merely replace the position loop with torque regulation, the proposed method introduces a disturbance-estimation-driven synchronization architecture co-designed with deterministic EtherCAT cyclic timing, which enables distributed real-time compensation beyond classical torque feedforward strategies. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Motor Control, Drives and Power Electronics)
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19 pages, 2940 KB  
Article
Monitoring and Diagnostics of Mining Electromechanical Equipment Based on Machine Learning
by Eduard Muratbakeev, Yuriy Kozhubaev, Diana Novak, Roman Ershov and Zhou Wei
Symmetry 2025, 17(9), 1548; https://doi.org/10.3390/sym17091548 - 16 Sep 2025
Cited by 12 | Viewed by 944
Abstract
Induction motors are a common component of electromechanical equipment in mining operations, yet they are susceptible to failures resulting from frequent start–stops, overloading, wear and tear, and component failure. It is evident that such failures can result in severe ramifications, encompassing industrial accidents [...] Read more.
Induction motors are a common component of electromechanical equipment in mining operations, yet they are susceptible to failures resulting from frequent start–stops, overloading, wear and tear, and component failure. It is evident that such failures can result in severe ramifications, encompassing industrial accidents and economic losses. The present paper proposes a detailed study of engine fault diagnosis technology. It has been demonstrated that prevailing intelligent engine diagnosis algorithms exhibit a limited diagnostic efficacy under variable operating conditions, and the reliability of diagnostic outcomes based on individual signals is questionable. The present paper puts forward the proposition of an investigation into a fault diagnosis algorithm for induction motors. This investigation utilized a range of analytical methods, including signal analysis, deep learning, transfer learning, and information fusion. Currently, the methods employed for fault diagnosis based on traditional machine learning are reliant on the selection of statistical features by those with expertise in the field, resulting in outcomes that are significantly influenced by human factors. This paper is the first to integrate a multi-branch ResNet strategy combining three-phase and single-phase currents. A range of three-phase current input strategies were developed, and a deep learning-based motor fault diagnosis model with adaptive feature extraction was established. This enables the deep residual network to extract fault depth features from the motor current signal more effectively. The experimental findings demonstrate that deep learning possesses the capacity to automatically extract depth features, thereby exceeding the capabilities of conventional machine learning algorithms with regard to the accuracy of motor fault diagnosis. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Motor Control, Drives and Power Electronics)
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17 pages, 9141 KB  
Article
Model-Free Generalized Super-Twisting Fast Terminal Sliding Mode Control for Permanent Magnet Synchronous Motors
by Xingyi Ma, Yu Xu, Lei Zhang and Jing Bai
Symmetry 2025, 17(1), 18; https://doi.org/10.3390/sym17010018 - 26 Dec 2024
Cited by 5 | Viewed by 1745
Abstract
Permanent Magnet Synchronous Motors (PMSMs) are nonlinear, multi-parameter systems that exhibit structural symmetry but are susceptible to parameter variations and external disturbances. These challenges can disrupt the inherent symmetrical characteristics of PMSM dynamics during real-world operations, posing difficulties for achieving efficient control. To [...] Read more.
Permanent Magnet Synchronous Motors (PMSMs) are nonlinear, multi-parameter systems that exhibit structural symmetry but are susceptible to parameter variations and external disturbances. These challenges can disrupt the inherent symmetrical characteristics of PMSM dynamics during real-world operations, posing difficulties for achieving efficient control. To address this issue, this paper proposes a Model-Free Generalized Super-Twisting Algorithm Fast Terminal Sliding Mode Control (MFFTSMC-GSTA) method. First, a novel ultra-local model incorporating PMSM uncertainties is established, and the MFFTSMC-GSTA controller is designed to address the system’s complex dynamic behavior. By integrating the generalized super-twisting algorithm with the nonsingular fast terminal sliding mode algorithm, the proposed controller ensures finite-time convergence and effectively mitigates chattering. Second, an extended sliding mode disturbance observer is developed to estimate the unknown components of the ultra-local model and provide feedforward compensation, further enhancing system robustness and dynamic performance. The experimental results show that the total harmonic distortion (THD) value of the proposed control method is 1.38%, demonstrating significant improvements in response speed and robustness for motor speed control, and verifying the algorithm’s superior performance under complex operating conditions. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Motor Control, Drives and Power Electronics)
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20 pages, 7147 KB  
Article
Motion Control of Macro–Micro Linear Platform Based on Adaptive Fuzzy Active Disturbance Rejection Control
by Mingyi Wang, Tianrun Kang, Kai Kang, Chengming Zhang and Liyi Li
Symmetry 2024, 16(6), 707; https://doi.org/10.3390/sym16060707 - 7 Jun 2024
Cited by 5 | Viewed by 4966
Abstract
To ensure precise positioning of the macro–micro platform with a symmetrical structure, it is crucial to mitigate the impact of various perturbations, including disturbances, as well as complex factors such as external loads, electrical noise, and model parameter variations. This paper proposes a [...] Read more.
To ensure precise positioning of the macro–micro platform with a symmetrical structure, it is crucial to mitigate the impact of various perturbations, including disturbances, as well as complex factors such as external loads, electrical noise, and model parameter variations. This paper proposes a novel macro–micro master–slave control structure that incorporates adaptive fuzzy linear active disturbance rejection control (AFLADRC). The Kp and Kd parameters of the linear state error feedback (LSEF) are dynamically tuned and adjusted using fuzzy reasoning. This approach enhances the robustness of the system and simplifies the tuning process. In addition, this paper also analyzes the symmetry of the coupling effect between macro and micro, as the coupling will affect the motor force and the reaction potential of the motor. The macro–micro platform adopts a symmetric design; the macro stage is driven by a permanent magnet synchronous linear motor (PMLSM), and the micro stage is driven by a voice coil motor. Finally, we built the macro–micro linear motion experimental platform to verify the control effect of the proposed method by conducting trajectory tracking experiments and comparison experiments. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Motor Control, Drives and Power Electronics)
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