Symbolic Testing of Diagnosability
Alban Grastien · ANU Open Research (Australian National University) · 2009
Abstract: Diagnosability ensures that the occurrence of a failure on the system can always be diagnosed by a diagnosis engine. In this paper, we explore symbolic techniques to test diagnosability of DES. We present several algorithms that can be implemented with symbolic tools, and show how to combine decentralised approach with symbolic approach. Finally, we discuss how to extract the minimal set of sensors that ensures diagnosability.