Special Issue "Mechatronic System for Automatic Control 2022"

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 1178

Special Issue Editors

Dr. Vadim R. Gasiyarov
E-Mail Website
Guest Editor
Mechatronics and Automation Department, South Ural State University, 454080 Chelyabinsk, Russia
Interests: power engineering; industrial mechatronic systems; automation; control systems
Special Issues, Collections and Topics in MDPI journals
Dr. Sergey M. Andreev
E-Mail Website
Guest Editor
Nosov Magnitogorsk State Technical University, 455000 Magnitogorsk, Russia
Interests: automation and control systems; optimal control system; data science; modeling; simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mechatronics systems are a part of industrial automated control systems. It is a synergetic combination of electrical, electronic units and precision mechanical parts, microprocessor technology, various energy sources, electric, hydraulic, and pneumatic drives. These units and parts are combined by intelligent control systems, focused on the contemporary automated industrial systems.

This Special Issue will accept innovative research and developments in mechatronics and automatic control. The overall objective is to render a wide range of disciplines, including power engineering; industrial mechatronic systems; automation and control systems. Emphasis is given to methods and findings aimed at determining the prospects for the development of smart industry technologies and the creation of promising technologies for the digital transformation of the industries.

Suitable topics for this Special Issue include, but are not limited to the following:

Industrial mechatronics and robotics;

Diagnostics and reliability of mechatronic systems;

Control systems and applications;

Sensors and computer vision;

Process automation;

Big data, machine learning, and artificial intelligence for Industry 4.0

Flexible manufacturing systems;

Digital twins technologies

Modeling and computer technologies for industrial applications.

Dr. Vadim R. Gasiyarov
Dr. Sergey M. Andreev
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. 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 1800 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.


  • Robotics and mechatronics
  • Automation and Control
  • Industry 4.0
  • Smart industry
  • Machine learning
  • Computer vision
  • Mechanism design
  • Electric, hydraulic, and pneumatic machines and drives

Published Papers (1 paper)

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Developing Digital Observer of Angular Gaps in Rolling Stand Mechatronic System
Machines 2022, 10(2), 141; https://doi.org/10.3390/machines10020141 - 16 Feb 2022
Cited by 1 | Viewed by 636
Algorithms for monitoring the rolling mill mechatronic system state should be developed on the basis of modern digital technologies. Developing digital shadows (observers) of system state parameters in the periodic measurement mode is promising. This study relevance is defined by frequent emergency breakdowns [...] Read more.
Algorithms for monitoring the rolling mill mechatronic system state should be developed on the basis of modern digital technologies. Developing digital shadows (observers) of system state parameters in the periodic measurement mode is promising. This study relevance is defined by frequent emergency breakdowns of rolling stand mechanical transmissions. Most breakdowns are caused by worn end clutches (heads) of countershafts (spindles) transmitting rotation from the motor to the rolls. This is caused by elastic oscillations due to closing angular gaps when the metal enters the stand. The spindle joint angular gap increases over time with the mill operation. Therefore, it is an important diagnostic parameter that allows for an estimation of the transmission serviceability. In this regard, the problem of monitoring the angular gaps in the rolling stand mechatronic systems is relevant. The paper considers developing an observer of angular gaps in the spindle joints of the ‘electric drive-stand’ mechatronic system of the plate Mill 5000 of Magnitogorsk Iron and Steel Works PJSC (MMK PJSC). The monitored signal (angular gap) is calculated with the mathematical processing of the motor’s physical parameters (speed and electromagnetic torque), measured at a given frequency. The gap is determined indirectly by integrating the speed during its closing. To achieve this, the speed is controlled according to the triangular tachogram at no load. The stand’s electromechanical system modes have been studied using mathematical simulation. The observer’s practical use expediency has been reasoned. The structure of the observer-based angular gap monitoring information system is given. The system has been full-scale tested on Mill 5000, which has confirmed the developed algorithm efficiency. The study’s contribution is a justified and implemented concept of a relatively simple technical solution that can be commercially implemented without extra costs. The angular gap calculation algorithm does not involve complex mathematical techniques and can be implemented in industrial rolling mill controllers. Monitoring is automated without human involvement, which eliminates the human factor. The solution has a specific practical focus and is recommended for implementation at operating rolling mills. Full article
(This article belongs to the Special Issue Mechatronic System for Automatic Control 2022)
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