Advances in Fault Diagnosis and Fault-Tolerant Control: From Classical Approaches to AI-Driven Solutions
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Signal and Data Analysis".
Deadline for manuscript submissions: 30 January 2026 | Viewed by 18
Special Issue Editor
Interests: fault-tolerant control; MPC; data-driven control; reinforcement learning; building automaton; energy efficiency
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Ensuring the safe and reliable operation of complex engineering systems requires robust strategies for identifying, isolating, and mitigating faults. This Special Issue of Entropy aims to collate recent developments related to Fault Diagnosis and Fault-Tolerant Control (FD/FTC), spanning both classical model-based methods and cutting-edge data-driven or AI-based approaches.
Topics of interest include model-based FDD, machine learning and deep learning for fault detection, reinforcement learning for FTC, uncertainty quantification, and entropy-based evaluation metrics. We particularly welcome works that bridge information theory and control or provide novel theoretical insights, algorithmic innovations, or validated industrial case studies.
We encourage submissions from researchers working in automation, aerospace, energy systems, transportation, and other domains where fault resilience is key. Original research articles, reviews, and benchmark and comparative studies are all welcome to be submitted.
Topics of interest include, but are not limited to, the following:
- Model-based fault detection, isolation, and diagnosis;
- Data-driven fault diagnosis using machine learning or statistical methods;
- AI-based approaches: deep learning, transfer learning, and graph-based FDD;
- Information–theoretic analysis of fault signals and decision thresholds;
- Model-based and adaptive fault-tolerant control schemes;
- Reinforcement learning and online FTC algorithms;
- Uncertainty quantification in fault detection and control;
- Fault accommodation, reconfiguration, and recovery strategies;
- Applications of FD/FTC in industrial, autonomous, and energy systems;
- Comparative studies and benchmarking on FD/FTC methods.
Dr. Joseph J. Yame
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. Entropy 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 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
- fault detection and diagnosis (FDD)
- fault-tolerant control (FTC)
- model-based methods
- data-driven control
- machine learning for control systems
- reinforcement learning
- uncertainty quantification
- information–theoretic analysis
- control reconfiguration
- cyber–physical systems’ resilience
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