Qualitative reasoning: modeling and simulation with incomplete knowledge
Qualitative reasoning: modeling and simulation with incomplete knowledge
Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Robust Control: The Parametric Approach
Robust Control: The Parametric Approach
Bounding Approaches to System Identification
Bounding Approaches to System Identification
Optimal Real-time Control of Sewer Networks (Advances in Industrial Control)
Optimal Real-time Control of Sewer Networks (Advances in Industrial Control)
Brief paper: Parity relations for linear uncertain dynamic systems
Automatica (Journal of IFAC)
SQualTrack: a tool for robust fault detection
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nonlinear predictive control using constraints satisfaction
COCOS'03 Proceedings of the Second international conference on Global Optimization and Constraint Satisfaction
Online monitoring by dynamically refining imprecise models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Brief paper: Recursive state bounding by parallelotopes
Automatica (Journal of IFAC)
Survey Research on gain scheduling
Automatica (Journal of IFAC)
Brief Robust fault detection in uncertain dynamic systems
Automatica (Journal of IFAC)
Brief Causal fault detection and isolation based on a set-membership approach
Automatica (Journal of IFAC)
Brief Guaranteed state estimation by zonotopes
Automatica (Journal of IFAC)
Performance Evaluation Based Fault Tolerant Controlwith Actuator Saturation Avoidance
International Journal of Applied Mathematics and Computer Science - Issues in Advanced Control and Diagnosis
Stability analysis of the neural network based fault tolerant control for the boiler unit
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Passive robust fault detection using RBF neural modeling based on set membership identification
Engineering Applications of Artificial Intelligence
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This paper reviews the use of set-membership methods in fault diagnosis (FD) and fault tolerant control (FTC). Setmembership methods use a deterministic unknown-but-bounded description of noise and parametric uncertainty (interval models). These methods aims at checking the consistency between observed and predicted behaviour by using simple sets to approximate the exact set of possible behaviour (in the parameter or the state space). When an inconsistency is detected between the measured and predicted behaviours obtained using a faultless system model, a fault can be indicated. Otherwise, nothing can be stated. The same principle can be used to identify interval models for fault detection and to develop methods for fault tolerance evaluation. Finally, some real applications will be used to illustrate the usefulness and performance of set-membership methods for FD and FTC.