Diagnosis and Automata

  • Eric Fabre
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 433)


Fault diagnosis and state estimation are two central and typical problems one may face in the monitoring of discrete-event systems. This chapter examines these two problems in the simple setting of automata. It is first explained that diagnosis and state estimation are two related problems. Then one describes the construction of an observer (resp. a diagnoser) both for standard and for probabilistic automata. A section is dedicated to diagnosability issues, that is the ability to detect the occurrence of an unobservable fault event after a bounded number of observations following that fault. The chapter then proposes an opening to the case of distributed systems, made of several interacting components, but still assuming a sequential semantics (i.e. ignoring the possible parallelism of some events). One first presents a modularity property on observers and diagnosers of distributed systems, in a rather specific case. The general case is then examined, and a distributed procedure is described to recover the runs of a distributed system that can explain a set of distributed observations collected in this system. Finally, the chapter closes on a discussion about the interest of true concurrency semantics for the monitoring of large distributed systems.


State Estimation Discrete Event System Label Function Visible Transition Faulty State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.INRIA Rennes Bretagne AtlantiqueRennes cedexFrance

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