Selected Papers from the 8th International Conference on Control, Automation and Diagnosis (ICCAD 2024)

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

Deadline for manuscript submissions: closed (30 November 2024) | Viewed by 936

Special Issue Editor


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Guest Editor
Computer Science, Université Grenoble Alpes, Grenoble, France
Interests: diagnostic; prognostic; maintenance; reliability; safety

Special Issue Information

Dear Colleagues,

ICCAD 2024 conference is a forum for presenting excellent results and new challenges in the field of the reliability and availability of control, automation and diagnosis. It brings together experts from industry, government and academia, experienced in engineering, design and research. This conference will provide a remarkable opportunity for the academic and industrial communities to address new challenges, share solutions and discuss future research directions. The technical program will include plenary lectures, regular technical sessions and special sessions. The conference covers both classic and most recent trends in control, automation and diagnosis, addressing both theoretical and applicative aspects, with particular emphasis on (but not limited to) the following topics:

  • computational intelligence
  • human–machine interactions
  • artificial intelligence methods for diagnosis
  • renewable energy and green transportation
  • reliability

Prof. Dr. Zineb SIMEU-ABAZI
Guest Editor

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Keywords

  • computational intelligence
  • human–machine interactions
  • artificial intelligence methods for diagnosis
  • renewable energy and green transportation
  • reliability

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Published Papers (1 paper)

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Research

17 pages, 337 KiB  
Article
Linear Matrix Inequalities in Fault Detection Filter Design for Linear Ostensible Metzler Systems
by Dušan Krokavec and Anna Filasová
Machines 2025, 13(1), 46; https://doi.org/10.3390/machines13010046 - 10 Jan 2025
Viewed by 548
Abstract
The article deals with the properties of fault detection filters when applying their structure to a class of linear, continuous-time systems, with dynamics being specified by the system matrix of the ostensible Metzler structure. The proposed solution is reduced to the use of [...] Read more.
The article deals with the properties of fault detection filters when applying their structure to a class of linear, continuous-time systems, with dynamics being specified by the system matrix of the ostensible Metzler structure. The proposed solution is reduced to the use of diagonal stabilization in the synthesis of the state observer and uses the decomposition of the ostensible Metzler matrix. The approach creates a unified framework that covers the compactness of parametric constraints on Metzler matrices and their quadratic stability. Due to the complexity of such constraints, the design conditions are formulated using sharp linear matrix inequalities. For potential application in network control structures, the problem is formulated and solved for linear discrete-time ostensible positive systems. Finally, a linearized model of the B747-100/200 aircraft is used to validate the proposed method. The numerical solution and simulation results show that the proposed approach provides superior sensitivity of the fault detection filter in detecting faults, compared to synthesis methods that do not guarantee the positivity of the filter gain. Full article
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