Session 6: DES Control

Session chair: Maria Pia Fanti 

16:30 - 18:00 Thursday 5th September 2013
16:30 Computation of Fault-Tolerant Supervisors for Discrete Event Systems
Authors: Ayse Nur Sulek, Klaus Schmidt
Abstract: Fault-tolerance addresses the problem of operating a system even in case of faults. In this paper, we study fault-tolerance in the supervisory control framework for discrete event systems (DES). We consider DES, where certain events might no longer be possible in case a fault happens. In this setting, we first identify necessary and sufficient conditions for the existence of a supervisor that realizes a given behavioral specification both in the non-faulty and in the faulty case. We further show that it is possible to determine a supremal fault-tolerant sublanguage in case the existence condition is violated. Finally, we propose an algorithm for the computation of this sublanguage and prove its correctness. Different from existing work, our fault-tolerant supervisor allows fault occurrences and system repairs at any time. The concepts and results developed in this paper are illustrated by a manufacturing system example. 
17:00 Heuristic Search of Supervisors by Approximated Distinguishers
Authors: Raquel Stella Silva Aguiar, Antonio Eduardo Carrilho da Cunha, Jose E. R. Cury, Max H. de Queiroz
Abstract: The use of distinguishers was introduced for Supervisory Control Theory (SCT) in order to simplify the task of modeling speci cations, while guaranteeing the synthesis of maximally permissive supervisors. On the other hand, by approximating the language of a distinguisher, a supervisor can be obtained with computational savings in the synthesis, although there is no guarantee that this is the maximally permissive solution. The main purpose of this work is to propose a procedure to obtain the least restrictive achievable supervisor, in the context of approximations in the SCT with distinguishers. The procedure consists of a heuristic search for the supervisor with the highest language measure in the space formed by supervisors obtained using approximated distinguishers. A search procedure based in Genetic Algorithms was implemented and a case study illustrates the results of the method.