Sensor Minimization Problems with Static or Dynamic Observers for Fault Diagnosis

We study sensor minimization problems in the context of fault diagnosis. Fault diagnosis consists in synthesizing a diagnoser that observes a given plant and identifies faults in the plant as soon as possible after their occurrence. Existing literature on this problem has considered the case of static observers, where the set of observable events does not change during execution of the system. In this paper, we consider static as well as dynamic observers, where the observer can “switch” sensors on or off, thus dynamically changing the set of events it wishes to observe. It is known that checking diagnosability (whether an observer capable of identifying faults exists) can be solved in polynomial time for static observers, and we show that the same is true for dynamic ones. On the other hand, minimizing the number of (static) observable events required to achieve diagnosability is NP-complete. We show that this is true also in the case of mask-based observation, where some event...

• Type: Conference
• Year: 2007
• Where: ACSD
• Authors: Franck Cassez, Stavros Tripakis, Karine Altisen
• Keywords: ACSD 2007, Dynamic Observers, Fault Diagnosis, Hardware, Static Observers