Data-Driven Anomaly Recognition for Unsupervised Model-Free Fault Detection in Artificial Pancreas.
Lorenzo MeneghettiMatteo TerziSimone Del FaveroGian Antonio SustoClaudio CobelliPublished in: IEEE Trans. Control. Syst. Technol. (2020)
Keyphrases
- fault detection
- model free
- data driven
- reinforcement learning
- fault diagnosis
- fault identification
- industrial processes
- temporal difference
- reinforcement learning algorithms
- function approximation
- policy iteration
- condition monitoring
- pattern recognition
- fault detection and diagnosis
- robust fault detection
- failure detection
- tennessee eastman
- unsupervised learning
- neural network
- anomaly detection
- fuel cell
- feature extraction
- fault detection and isolation
- power plant
- computational intelligence
- least squares
- active learning
- training set
- impedance control
- genetic algorithm
- real world