Diagnosis of higher-order discrete-event systems

Preventing major events, like the India blackout in 2012 or the Fukushima nuclear disaster in 2011, is vital for the safety of society. Automated diagnosis may play an important role in this prevention. However, a gap still exists between the complexity of systems such these and the effectiveness of state-of-the-art diagnosis techniques. The contribution of this paper is twofold: the definition of a novel class of discrete-event systems (DESs), called higher-order DESs (HDESs), and the formalization of a relevant diagnosis technique. HDESs are structured hierarchically in several cohabiting subsystems, accommodated at different abstraction levels, each one living its own life, as happens in living beings. The communication between subsystems at different levels relies on complex events, occurring when specific patterns of transitions are matched. Diagnosis of HDESs is scalable, context-sensitive, and in a way intelligent

Specification and model-based diagnosis of higher-order discrete-event systems

A novel class of discrete-event systems, called higher-order DESs (HDESs) is introduced, along with a relevant diagnosis technique. The behavior of a HDES is stratified, resulting in a hierarchy of cohabiting sub-DESs, each one living its own life. The communication between subsystems at different levels of abstraction relies on complex events, occurring when specific patterns of transitions are matched. Separation of concerns is achieved and the expressive power of diagnosis, which is scalable and context-sensitive, is enhanced