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Sensing and Control Technology for Intelligent Machine
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Sensing and Control Technology for Intelligent Machine

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 5566

Special Issue Editors

Prof. Dr. Feng Sun

E-Mail Website
Guest Editor
School of Mechanical Engineering, Shenyang University of Technology, Shenyang 110870, China
Interests: Magnetic levitation technology;Magnetic bearings;Magnetic actuators applications;Active vehicle suspension using magnetic actuators
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zhiqiang Long

E-Mail Website
Guest Editor
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Interests: maglev train technology; maglev bearing technology; maglev control technology; fault diagnosis and fault-tolerant control; electromechanical system safety control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Weijun Liu

E-Mail Website
Guest Editor
School of Mechanical Engineering, Shenyang University of Technology, Shenyang 110870, China
Interests: sensing in additive manufacturing; laser cleaning; laser shock processing; CNC machining
Prof. Dr. Guobin Lin

E-Mail Website
Guest Editor
The National Maglev Transportation Engineering R&D Center, Tongji University, Shanghai 201804, China
Interests: maglev vehicle research; linear drive
Dr. Yuanping Xu

E-Mail Website
Guest Editor
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: magnetic levitation; smart sensors and actuators; vibration control; rotordynamics

Special Issue Information

Dear Colleagues,

Sensing technology and control are two key points to ensure the operation of intelligent mechanical systems. Through sensing detection, the operation information of the intelligent mechanical system can be effectively realized, and the corresponding useful signal can be converted to output. The perfect combination of sensing signals and control algorithms can effectively improve various defects in intelligent mechanical system. For example, in the magnetic levitation system, the position signal of the air-gap and the optimal control theory are the keys to ensure the system levitation. Therefore, sensing and control technology for intelligent machines have attracted the extensive attention of scholars at home and abroad, and have become a research hotspot in related fields. In order to solve the basic scientific problems and key technical problems related to sensing and control technology, and gather the frontier achievements of intelligent machine sensing and control, Sensors has set up a Special Issue, entitled " Sensing and control technology for intelligent machine".

This Special Issue is addressed to all types of techniques for intelligent machine sensors and control.

Prof. Dr. Feng Sun
Prof. Dr. Zhiqiang Long
Prof. Dr. Weijun Liu
Prof. Dr. Guobin Lin
Dr. Yuanping Xu
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. Sensors 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

  • sensing and control technology for magnetic levitation
  • sensing and control technology for magnetic actuators
  • smart sensors
  • mechatronics devices for sensors
  • applications of sensors for robotics and mechatronics devices
  • control
  • automation
  • intelligent mechatronic systems

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

Published Papers (2 papers)

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Research

15 pages, 5831 KiB  
Article
Measurement of Magnetic and Magnetostrictive Characteristics of Transformer Core Based on Triaxial Strain Gauge and B-H Vector Sensor
by Zhen Wang, Zheming Fan, Xiang Li, Kai Xu and Runjie Yu
Sensors 2023, 23(13), 5926; https://doi.org/10.3390/s23135926 - 26 Jun 2023
Cited by 2 | Viewed by 1584
Abstract
As is well known, the magnetostrictive phenomenon of electrical steel sheet is the main source of electricity in equipment such as transformers. The magnetostrictive characteristic of the actual transformer core is more complicated than that of single-sheet steel. The magnetostriction phenomenon of the [...] Read more.
As is well known, the magnetostrictive phenomenon of electrical steel sheet is the main source of electricity in equipment such as transformers. The magnetostrictive characteristic of the actual transformer core is more complicated than that of single-sheet steel. The magnetostriction phenomenon of the transformer core cannot be fully understood by studying only a single piece of electrical steel, so it is necessary to study the local magnetic characteristics of the transformer directly. In this paper, two-limb, one-phase transformer core with a multi-step-lap construction was assembled, a laminated magnetostrictive testing system based on triaxial strain gauges was built, and the local magnetic characteristics were studied using a self-developed B-H vector sensor. The magnetostrictive and magnetic properties in different local regions were measured and analyzed under several magnetization patterns, and the influence of DC bias on the magnetostrictive property of the corner, yoke, and limb of the core was investigated. The influence of the position of the clamp on the magnetostriction of the transformer core was also studied. The magnetostrictive strain of the single sheet and laminated core was compared and discussed. The results showed that the strain caused by the interaction between laminations in this area can be effectively reduced when clamping in the middle of the yoke. Full article
(This article belongs to the Special Issue Sensing and Control Technology for Intelligent Machine)
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26 pages, 6656 KiB  
Article
Vehicle Stability Analysis under Extreme Operating Conditions Based on LQR Control
by Liping Wu, Ran Zhou, Junshan Bao, Guang Yang, Feng Sun, Fangchao Xu, Junjie Jin, Qi Zhang, Weikang Jiang and Xiaoyou Zhang
Sensors 2022, 22(24), 9791; https://doi.org/10.3390/s22249791 - 13 Dec 2022
Cited by 10 | Viewed by 3014
Abstract
Under extreme working conditions such as high-speed driving on roads with a large road surface unevenness coefficient, turning on a road with a low road surface adhesion coefficient, and emergency acceleration and braking, a vehicle’s stability deteriorates sharply and reduces ride comfort. There [...] Read more.
Under extreme working conditions such as high-speed driving on roads with a large road surface unevenness coefficient, turning on a road with a low road surface adhesion coefficient, and emergency acceleration and braking, a vehicle’s stability deteriorates sharply and reduces ride comfort. There is extensive existing research on vehicle active suspension control, trajectory tracking, and control methods. However, most of these studies focus on conventional operating conditions, while vehicle stability analysis under extreme operating conditions is much less studied. In order to improve the stability of the whole vehicle under extreme operating conditions, this paper investigates the stability of a vehicle under extreme operating conditions based on linear quadratic regulator (LQR) control. First, a seven degrees of freedom (7-DOF) dynamics model of the whole vehicle is established based on the use of electromagnetic active suspension, and then an LQR controller of the electromagnetic active suspension is designed. A joint simulation platform incorporating MATLAB and CarSim was built, and the CarSim model is verified by real vehicle tests. Finally, the stability of the vehicle under four different ultimate operating conditions was analyzed. The simulation results show that the root mean square (RMS) values of body droop acceleration and pitch angle acceleration are improved by 57.48% and 28.81%, respectively, under high-speed driving conditions on Class C roads. Under the double-shift condition with a low adhesion coefficient, the RMS values of body droop acceleration, pitch acceleration, and roll angle acceleration are improved by 58.25%, 55.41%, and 31.39%, respectively. These results indicate that electromagnetic active suspension can significantly improve vehicle stability and reduce driving risk under extreme working conditions when combined with an LQR controller. Full article
(This article belongs to the Special Issue Sensing and Control Technology for Intelligent Machine)
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