A New Product Construction for the Diagnosability of Patterns in Time Petri Net


We propose a method to decide the diagnosability of patterns in labeled Time Petri nets (TPN) that gracefully extends a classic approach for the diagnosability of single faults. Our approach is based on a new technique for computing the language intersection of TPN and on an associated extension of the State Class Graph construction. Our approach has been implemented and we report on some experimental results.

In CDC 202059th IEEE Conference on Decision and Control