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Machines
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Design and Control of Electrical Machines II
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Design and Control of Electrical Machines II

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Electrical Machines and Drives".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 11756

Special Issue Editors

Prof. Dr. Fu-Cheng Wang

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Guest Editor
Department of Mechanical Engineering, National Taiwan University, Taipei 10617, Taiwan
Interests: robust control;vibration control; system integration; medical engineering;energy systems
Special Issues, Collections and Topics in MDPI journals
Dr. Yi-Liang Yeh

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Taipei University of Technology, Taipei 106344, Taiwan
Interests: control theory design and applications; sliding-mode control; robust observer; mechatronic systems; piezo control
Dr. Yu-Hsiu Lee

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Taiwan University, Taipei, Taiwan
Interests: precision electromechanical systems; modeling and motion control of mechanical systems; medical robotics; adaptive and learning control
Dr. I-Haur Tsai

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
Interests: robust control; mechatronics; control theory; intelligent control; automatic control; artificial intelligence

Special Issue Information

Dear Colleagues,

Following the success of the previous Special Issue “Design and Control of Electrical Machines” (https://www.mdpi.com/journal/machines/special_issues/control_machines), we are pleased to announce the next in the series, entitled “ Design and Control of Electrical Machines II”. 

Electrical machines play an important role in modern industry. Novel design and advanced control strategies have contributed to the performance improvements of electrical machines and their applications, such as motors, electric vehicles, and power devices. New techniques have also emerged for the control of electrical machines, including artificial intelligence, wireless sensor networks, internet of things, and big data analysis. This Special Issue focuses on the advances related to electrical machines, such as novel designs; novel control strategies; and new technologies including WSNs, IoT, artificial intelligence, new applications, etc. Papers related to electrical machines in this field are most welcome. Topics of interest for publication include, but are not limited to:

  • Novel design of electrical machines.
  • New system architectures and technologies.
  • Electric vehicles, including land, sea, and air vehicles.
  • Applications of electrical machines.
  • Modelling and control of electrical machines and systems.
  • Power devices and systems.
  • Advanced control and optimization algorithms for electrical power systems.
  • Application of WSNs, IoT, and artificial intelligence in electrical machines and systems.

Prof. Dr. Fu-Cheng Wang
Dr. Yi-Liang Yeh
Dr. Yu-Hsiu Lee
Dr. I-Haur Tsai
Guest Editor

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. Machines 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

  • electrical machines and systems
  • novel design
  • advanced control
  • wireless sensor network
  • internet of things
  • artificial intelligence
  • electric vehicles
  • power devices
  • power systems
  • applications

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

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Research

17 pages, 7131 KiB  
Article
Regression Model for the Prediction of Total Motor Power Used by an Industrial Robot Manipulator during Operation
by Sandi Baressi Šegota, Nikola Anđelić, Jelena Štifanić and Zlatan Car
Machines 2024, 12(4), 225; https://doi.org/10.3390/machines12040225 - 28 Mar 2024
Viewed by 1087
Abstract
Motor power models are a key tool in robotics for modeling and simulations related to control and optimization. The authors collect the dataset of motor power using the ABB IRB 120 industrial robot. This paper applies a multilayer perceptron (MLP) model to the [...] Read more.
Motor power models are a key tool in robotics for modeling and simulations related to control and optimization. The authors collect the dataset of motor power using the ABB IRB 120 industrial robot. This paper applies a multilayer perceptron (MLP) model to the collected dataset. Before the training of MLP models, each of the variables in the dataset is evaluated using the random forest (RF) model, observing two metrics-mean decrease in impurity (MDI) and feature permutation score difference (FP). Pearson’s correlation coefficient was also applied Based on the scores of these values, a total of 15 variables, mainly static variables connected with the position and orientation of the robot, are eliminated from the dataset. The scores demonstrate that while both MLPs achieve good scores, the model trained on the pruned dataset performs better. With the model trained on the pruned dataset achieving R¯2=0.99924,σ=0.00007 and MA¯PE=0.33589,σ=0.00955, the model trained on the original, non-pruned, data achieves R¯2=0.98796,σ=0.00081 and MA¯PE=0.46895,σ=0.05636. These scores show that by eliminating the variables with a low influence from the dataset, a higher scoring model is achieved, and the created model achieves a better generalization performance across five folds used for evaluation. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines II)
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20 pages, 6388 KiB  
Article
Control Design for a Power-Assisted Mobile Trainer: Applied to Clinical Stroke Rehabilitation
by Fu-Cheng Wang, Wei-Ren Pan, Chung-Hsien Lee, Szu-Fu Chen, Ang-Chieh Lin, Lin-Yen Cheng and Tzu-Tung Lin
Machines 2024, 12(1), 61; https://doi.org/10.3390/machines12010061 - 15 Jan 2024
Viewed by 1355
Abstract
This paper presents control design and implementation for a power-assisted mobile trainer that employs neuro-developmental treatment (NDT) principles. NDT is a gait rehabilitation technique for stroke patients that provides minimum intervention at critical gait events. Traditional NDT rehabilitation is an effective post-stroke treatment [...] Read more.
This paper presents control design and implementation for a power-assisted mobile trainer that employs neuro-developmental treatment (NDT) principles. NDT is a gait rehabilitation technique for stroke patients that provides minimum intervention at critical gait events. Traditional NDT rehabilitation is an effective post-stroke treatment but is also time consuming and labor intensive for therapists. Therefore, we designed a mobile NDT trainer to automatically repeat therapists’ intervention patterns, allowing patients to receive sufficient training without increasing therapists’ workloads. Because the trainer was self-propelled, it could cause burdens to stroke patients with limited muscle strength, thereby potentially degrading the rehabilitation effects. Hence, this paper proposes a power-assisted device that can let the mobile trainer follow the user, allowing the subject to focus on the rehabilitation training. We conducted system identification and control design for the power-assisted NDT trainer. We then implemented the designed controllers and tested the trainer. Finally, we invited 10 healthy subjects and 12 stroke patients to conduct clinical experiments. After using the power-assisted NDT trainer, most participants exhibited improvements in swing-phase symmetry, pelvic rotation, and walking speed. Based on the results, the power-assisted device was deemed effective in facilitating stroke rehabilitation. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines II)
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13 pages, 3082 KiB  
Article
Verification of a Newly Developed Mobile Robot’s Actuator Parameters
by Ján Semjon, Rudolf Jánoš, Marek Sukop, Peter Tuleja, Peter Marcinko and Marek Nowakowski
Machines 2023, 11(3), 411; https://doi.org/10.3390/machines11030411 - 22 Mar 2023
Cited by 2 | Viewed by 1558
Abstract
This paper addresses the issue of the verification and comparison of the selected properties of a newly developed electric actuator. This actuator is intended to act as the drive of a walking robot designed for robotic football. Its envisioned placement is inside the [...] Read more.
This paper addresses the issue of the verification and comparison of the selected properties of a newly developed electric actuator. This actuator is intended to act as the drive of a walking robot designed for robotic football. Its envisioned placement is inside the robot’s knee joint and in its upper part. An integral part of the actuator is a harmonic precision gearbox and an absolute rotation sensor. The prototype of the newly developed actuator consists of both aluminum and 3D-printed parts. The selected parameters were verified according to the selected characteristics of ISO standard 9283, namely a one-directional pose accuracy and repeatable pose accuracy. The obtained data were compared with those of the standard actuator used thus far in constructing robots for robotic football. The implemented verification is based on the need to improve the performance parameters of the actuator while ensuring the sufficient accuracy of stopping the actuator in the required position. This is ensured by the use of a more accurate harmonic reducer and rotation sensor compared to the standard actuator. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines II)
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24 pages, 6111 KiB  
Article
Manipulator Trajectory Optimization Using Reinforcement Learning on a Reduced-Order Dynamic Model with Deep Neural Network Compensation
by Yung-Hsiu Chen, Wu-Te Yang, Bo-Hsun Chen and Pei-Chun Lin
Machines 2023, 11(3), 350; https://doi.org/10.3390/machines11030350 - 3 Mar 2023
Cited by 3 | Viewed by 3411
Abstract
This article reports the construction of an articulated manipulator’s hybrid dynamic model and trajectory planning and optimization of the manipulator using deep reinforcement learning (RL) on the dynamic model. The hybrid model was composed of a physical-based reduced-order dynamic model, linear friction and [...] Read more.
This article reports the construction of an articulated manipulator’s hybrid dynamic model and trajectory planning and optimization of the manipulator using deep reinforcement learning (RL) on the dynamic model. The hybrid model was composed of a physical-based reduced-order dynamic model, linear friction and damping terms, and a deep neural network model to compensate for the nonlinear characteristics of the manipulator. The hybrid model then served as the digital twin of the manipulator for trajectory planning to optimize energy efficiency and operation speed by using RL while taking obstacle avoidance into consideration. The proposed strategy was simulated and experimentally validated. The energy consumption along paths was reduced and the speed was increased so the manipulator could achieve more efficient motion. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines II)
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12 pages, 2704 KiB  
Article
Model-Free Output-Feedback Sliding-Mode Control Design for Piezo-Actuated Stage
by Yi-Liang Yeh, Hsuan-Wei Pan and Yuan-Hong Shen
Machines 2023, 11(2), 152; https://doi.org/10.3390/machines11020152 - 22 Jan 2023
Cited by 1 | Viewed by 1528
Abstract
Hysteresis in a piezoelectric actuator must be compensated for, and this compensation constitutes the main challenge in the high-precision motion control of piezo-actuated stages. This paper presents an output-feedback sliding-mode control (SMC) scheme to suppress unknown nonlinearity; in this scheme, hysteresis behavior is [...] Read more.
Hysteresis in a piezoelectric actuator must be compensated for, and this compensation constitutes the main challenge in the high-precision motion control of piezo-actuated stages. This paper presents an output-feedback sliding-mode control (SMC) scheme to suppress unknown nonlinearity; in this scheme, hysteresis behavior is considered an external disturbance, and complex hysteresis models are thus not required. The scheme functions in the absence of transfer function of system state information, and a robust loop-transfer recovery observer is employed as a noise-free differentiator to estimate the required signal derivatives when the relevant system is in a noisy environment. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines II)
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14 pages, 4683 KiB  
Article
Disturbance Observer-Based Sliding Mode Controller for Underwater Electro-Hydrostatic Actuator Affected by Seawater Pressure
by Yong Nie, Zhenhua Lao, Jiajia Liu, Yichi Huang, Xiangwei Sun, Jianzhong Tang and Zheng Chen
Machines 2022, 10(12), 1115; https://doi.org/10.3390/machines10121115 - 24 Nov 2022
Cited by 2 | Viewed by 1729
Abstract
This paper presents a disturbance-observer-based sliding mode control strategy for an underwater electro-hydrostatic actuator, particularly considering that electro-hydrostatic actuators (EHAs) significantly suffer from sea pressure disturbance, which makes it hard to achieve high-precision position control. Therefore, a nonlinear disturbance observer was designed to [...] Read more.
This paper presents a disturbance-observer-based sliding mode control strategy for an underwater electro-hydrostatic actuator, particularly considering that electro-hydrostatic actuators (EHAs) significantly suffer from sea pressure disturbance, which makes it hard to achieve high-precision position control. Therefore, a nonlinear disturbance observer was designed to aim at the matched and mismatched disturbance caused by sea pressure disturbance. Then, a nonlinearities model for an underwater EHA was established, and a related non-singular fast terminal sliding mode (NFTSM) controller was designed by changing the conventional sliding mode surface to further improve the control accuracy. In addition, the backstepping tool was used to guarantee the robust stability of the entire three-order hydraulic dynamic system. Finally, a comparative simulation was conducted with different load forces in AMESim and Simulink, which effectively verified the high tracking performance of the proposed control strategy. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines II)
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