Advanced Fault-Tolerant Control Techniques for Complex Industrial Processes

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 2518

Special Issue Editors

Department of Control Science and Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: big data; machine learning; advanced control; fault diagnosis with application to hot rolling mill
Special Issues, Collections and Topics in MDPI journals
Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing, 100871, China
Interests: fault diagnosis; fault tolerant control
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: performance monitoring; fault diagnosis; fault-tolerant control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid development of computer technique, electronics, and information technology, modern industrial processes are generally becoming more and more complex. For such processes, the safety and reliability issues are of significant importance, since fault or failure may result in disastrous consequences and hazards for personnel, plant, and environment, particularly when the systems are embedded in safety-relevant plants like networks, robots, or power plants. As a consequence, fault-tolerant control (FTC) techniques have received considerable attention both in industry and academia over the past several decades. However, the capabilities of the traditional FTC methods are significantly degraded when the faults are encountered in highly complex industrial processes. This motivates the development of more advanced FTC methodologies to provide effectual actions for process recovery and life-circle management. So far, there are many complex and challenging issues in the FTC techniques, such as data-driven performance recovery methodologies, advanced model-based FTC techniques, as well as machine-learning-aided FTC techniques and their application in complex industrial processes and safety-relevant processes.

This Special Issue will focus on advanced process recovery and fault-tolerant control methodologies for complex industrial systems, especially process monitoring and fault-tolerant control techniques and machine-learning-related schemes, with their industrial applications. The Guest Editors invite original manuscripts presenting recent advances in these fields, with special reference to the following topics:

  • Data-driven performance monitoring and recovery techniques.
  • Machine-learning-based performance optimization and FTC techniques.
  • New FTC techniques for highly nonlinear systems.
  • Advanced model-based FTC techniques for complex industrial processes.
  • Intelligent FTC techniques for safe-critical systems.
  • Event-triggered FTC techniques.
  • Real-time implementation and industrial applications.

Prof. Dr. Kaixiang Peng
Prof. Dr. Ying Yang
Dr. Linlin Li
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. Information 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 1600 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

  • Fault-tolerant control
  • Performance recovery
  • Self-healing control
  • Fault resilient control
  • Process monitoring
  • Fault detection
  • Fault diagnosis
  • Fault prognosis
  • Operating performance assessment
  • Industrial process control

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

18 pages, 677 KiB  
Article
Observer-Based Active Fault-Tolerant Control of an Asymmetric Twin Wind Turbine
by Mariem Makni, Ihab Haidar, Jean-Pierre Barbot, Franck Plestan, Nabih Feki and Mohamed Slim Abbes
Information 2022, 13(3), 113; https://0-doi-org.brum.beds.ac.uk/10.3390/info13030113 - 25 Feb 2022
Cited by 2 | Viewed by 1961
Abstract
This paper deals with the design of an active fault-tolerant control based on observers for a twin wind turbine, consisting of two wind turbines mounted on the same tower. We consider an asymmetric conditions case, when only one turbine is affected by an [...] Read more.
This paper deals with the design of an active fault-tolerant control based on observers for a twin wind turbine, consisting of two wind turbines mounted on the same tower. We consider an asymmetric conditions case, when only one turbine is affected by an inter-turn short circuit fault of a permanent magnet synchronous machine. A diagnosis design is developed which combines the fault estimation method together with an active fault-tolerant control. The main advantage of the proposed method is to detect and correct the considered fault in a short time in order that the twin wind turbine behaves as it does in the healthy case. Full article
Show Figures

Figure 1

Back to TopTop