My interests are in the field of fault diagnosis in dynamic systems and in particular, since 1997, I am carrying out research into the development of methods for rapid detection and diagnosis of faults in input-output control sensors of industrial processes. The interest has been in the use of analytical redundancy methods based on information implicit in functional or analytical relationships which always exist between a number of measurements taken from a process (e.g. industrial plant). The research has exploited methods, using robust state observers, which have provided a capability for reliable detection of faults in the presence of typical plant parameter variations. These methods enable faults to be isolated, in addition to being detected. Furthermore, the reliable detection and isolation of multiple faults has also been experimented. I has worked on application studies ranging from industrial gas turbines and power plants (e.g. Pont sur le Sambre). The research is being driven by industrial application studies, although a particular interest has been the development of a unifying theory for model-based diagnosis algorithms. I am trying to apply the experimented methods within the context of robustness to uncertainty.
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