Invited session at IFAC WC 2023

Nom complet
AI enhanced fault detection, supervision and safety of technical processes

IFAC WC – Yokahama, Japan – 9 July to 14 July 2023

Invited Session: “AI enhanced fault detection, supervision and safety of technical processes”

IFAC TC 6.4 Fault Detection, Supervision & Safety of Technical Processes-SAFEPROCESS

Organizers :      Louise Travé-Massuyès, LAAS-CNRS & ANITI (louise@laas.fr )

                        Elodie Chanthery, LAAS-CNRS & ANITI, INSA de Toulouse (elodie.chanthery@laas.fr)

Please send your intention to contribute to this session before October 11th, 2022 with the following information: title, abstract, name of authors.

Papers must then be submitted following the standard procedure no later than October 30th on PaperCept with the code of the session (that will be provided by the IFAC WC organizers after the acceptance of the session).

It is now recognized that Control and Artificial Intelligence theories can be synergistically integrated to provide better solutions for fault detection, supervision, and safety of technical systems. Analytical models of phenomena and tasks along with formal AI methods provide reliable and explainable solutions. On the other hand, the learning abilities provided by machine and deep learning further bring new possibilities that have not yet all been explored. Today, we can aim to extract knowledge by data mining, to learn or update diagnosis models from historical data and, ultimately, to hybridate model-based and data-based approaches.

The main objective of this invited session is to create links between the Safeprocess and AI communities that could cross-fertilize the research on both sides. Technical contributions that aim at providing AI-enhanced solutions for fault detection, supervision and safety of technical processes are wellcome, together with survey, and application papers.

A non-exhaustive list of topics is provided below:

  • AI enhanced fault detection, isolation, estimation, and diagnosis,
  • AI enhanced predictive maintenance and supervision,
  • AI enhanced prognostics and health monitoring,
  • AI enhanced residual generation, residual evaluation,
  • AI enhanced anomaly detection and on-line change detection,
  • AI enhanced fault tolerant and cyber-secure control,
  • AI enhanced active diagnosis, decision making, system reconfiguration and fault accommodation,
  • AI enhanced severity and reliability analysis.