Learn More
The diagnosis of a discrete-event system is the problem of computing possible behaviors of the system given observations of the actual behavior, and testing whether the behaviors are normal or faulty. We show how the diagnosis problems can be translated into the propositional satisfiability problem (SAT) and solved by algorithms for SAT. Our experiments(More)
When dealing with real systems, it is unrealistic to suppose that observations can be totally ordered according to their emission dates. The partially ordered observations and the system are thus both represented as finite-state machines (or automata) and the diagnosis formally defined as the synchronized composition of the model with the observations. The(More)
It is well-known that the size of the model is a bottleneck when using model-based approaches to diagnose complex systems. To answer this problem, decentralised/distributed approaches have been proposed. Another problem, which is far less considered, is the size of the diagnosis itself. However , it can be huge enough, especially in the case of on-line(More)
—Recent years have witnessed significant interest in convex relaxations of the power flows, several papers showing that the second-order cone relaxation is tight for tree networks under various conditions on loads or voltages. This paper shows that AC-feasibility, i.e., to find whether some generator dispatch can satisfy a given demand, is NP-Hard for tree(More)
In the satisfiability domain, it is well-known that a SAT algorithm may solve a problem instance easily and another instance hardly, whilst these two instances are equivalent CNF encodings of the original problem. Moreover, different algorithms may disagree on which encoding makes the problem easier to solve. In this paper, we focus on the CNF encoding of(More)
We propose a theory of abstraction of discrete-event systems (DES) formulated at the semantic level, i.e., as a function that maps event traces at the original (ground) level to traces at the abstract level. We study how diagnosis of DES can be performed using an abstract model, and under which conditions this process leads to a correct solution (i.e., a(More)
We extend the decentralised/distributed approach of diagnosis of discrete-event systems modeled using automata. The goal is to avoid computing a global diagnosis, which is expensive, and to perform local diagnoses instead. To still ensure global consistency, we transform the topology of the system into a junction tree where each vertex represents a(More)