Dear colleagues,
we organized an open invited track on Intelligent data-driven fault diagnosis, prognostics and health aware control at IFAC World Congress 2023, Yokohama, Japan, see
https://www.ifac2023.org/media-download/95/39b83e6f22b8fb00/
- Submission code: 58mj9
- Submission deadline: 31 October 2022
The aim of this invited session is to foster the discussion and collaboration on algorithmic methodologies that leverage the production process data for fault diagnosis, estimation, condition monitoring, prognostics, and health-aware control. The session includes, but is not limited to, the following topics:
- Data-driven methods for designing residual generators for fault detection and isolation
- Data-driven methods for fault estimation
- Data-driven methods for prognostics and remaining useful life (RUL) estimation
- Health-aware control schemes and applications
- Transfer learning approaches to fault diagnosis
- Approaches for the inclusion of qualitative diagnostic information and operator experience
- Anomaly detection approaches in presence of unlabeled or unsecure data
- Reinforcement learning based approaches for control design of systems under deterioration.
Kind regards,
The proposers
