scholarly journals Adaptive Supervision of Patterns in Discrete Event Systems: Application to Crisis Management

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
M. Traore ◽  
M. Sayed-Mouchaweh ◽  
P. Billaudel
Keyword(s):  
Crisis Management ◽  
Discrete Event Systems ◽  
Discrete Event ◽  
Decision Makers ◽  
Finite State Automaton ◽  
Event Systems ◽  
Incomplete Model ◽  
Finite State ◽  
Important Challenge ◽  
System Approaches

Crisis management is currently an important challenge for medical service and research. This motivates the development of new decision system approaches to assist (or to guide) the decision makers. A crisis management is a special type of collaboration involving several actors. The context and characteristics of crisis such as extent of actors and their roles make the crisis management more difficult in order to take decision. In this paper, we propose to model the interaction between different actors involved in crisis management. For this purpose we use finite state automaton in order to optimize the emergency response to the crisis and to reduce the disastrous consequences on people and environment. Thus, an adaptive supervision method is proposed. Therefore, we address the problem of diagnosis and prediction (prognostic) given an incomplete model of the discrete event systems of a crisis situation. When the model is incomplete, we introduce learning into the diagnoser (diagnosis module) construction.

A Polynomial Algorithm for Diagnosability Analysis of Discrete Event Systems

2015 ◽  
Vol 6 (2) ◽  
pp. 1-22
Author(s):  
Eric Gascard ◽  
Zineb Simeu-Abazi ◽  
Bérangère Suiphon
Keyword(s):  
Discrete Event Systems ◽  
Discrete Event ◽  
Finite Sequence ◽  
Finite State Automaton ◽  
Bounded Number ◽  
Event Systems ◽  
Finite State ◽  
Definition Of ◽  
Necessary And Sufficient ◽  
Event Based

The paper deals with the definition of procedure that enables one to determine, for a given plant, if all faults can be detected and located after a finite sequence of observable events. More formally, the diagnosability is the property that every fault can be correctly detected from the observable events of the system after its occurrence no later than a bounded number of events. In this paper, the diagnosability problem of Discrete Event Systems (DESs) is studied. As modeling tool, finite-state automaton in an event-based framework is used. A necessary and sufficient condition of diagnosability of such systems is proposed. The results proposed in this paper allow checking the diagnosability of discrete event systems in an efficient way, i.e. in polynomial time.

A Petri Net Diagnoser for Discrete Event Systems Modeled by Finite State Automata

2015 ◽  
Vol 60 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Felipe Gomes Cabral ◽  
Marcos Vicente Moreira ◽  
Oumar Diene ◽  
Joao Carlos Basilio
Keyword(s):  
Petri Net ◽  
Discrete Event Systems ◽  
Discrete Event ◽  
Finite State Automata ◽  
Event Systems ◽  
Finite State

A Unified Method to Decentralized State Detection and Fault Diagnosis/prediction of Discrete-event Systems

2021 ◽  
Vol 181 (4) ◽  
pp. 339-371
Author(s):  
Kuize Zhang
Keyword(s):  
Fault Diagnosis ◽  
Discrete Event Systems ◽  
Discrete Event ◽  
Observation Time ◽  
Infinite Length ◽  
Event Systems ◽  
State Detection ◽  
Finite State ◽  
Common Observation ◽  
Unified Method

The state detection problem and fault diagnosis/prediction problem are fundamental topics in many areas. In this paper, we consider discrete-event systems (DESs) modeled by finite-state automata (FSAs). There exist plenty of results on decentralized versions of the latter problem but there is almost no result for a decentralized version of the former problem. In this paper, we propose a decentralized version of strong detectability called co-detectability which means that if a system satisfies this property, for each generated infinite-length event sequence, in at least one location the current and subsequent states can be determined by observations in the location after a common observation time delay. We prove that the problem of verifying co-detectability of deterministic FSAs is coNP-hard. Moreover, we use a unified concurrent-composition method to give PSPACE verification algorithms for co-detectability, co-diagnosability, and co-predictability of FSAs, without any assumption on or modification of the FSAs under consideration, where co-diagnosability is first studied by [Debouk & Lafortune & Teneketzis 2000], co-predictability is first studied by [Kumar & Takai 2010]. By our proposed unified method, one can see that in order to verify co-detectability, more technical difficulties will be met compared with verifying the other two properties, because in co-detectability, generated outputs are counted, but in the latter two properties, only occurrences of events are counted. For example, when one output was generated, any number of unobservable events could have occurred. PSPACE-hardness of verifying co-diagnosability is already known in the literature. In this paper, we prove PSPACE-hardness of verifying co-predictability.

scholarly journals DECIDABILITY AND COMPLEXITY ANALYSIS OF FORBIDDEN STATE PROBLEMS FOR DISCRETE EVENT SYSTEMS

2008 ◽  
Vol 19 (04) ◽  
pp. 999-1013 ◽  
Author(s):  
HSU-CHUN YEN
Keyword(s):  
Discrete Event Systems ◽  
Complexity Analysis ◽  
Discrete Event ◽  
Control Policy ◽  
State Problem ◽  
Event System ◽  
Event Systems ◽  
Complexity Issue ◽  
Finite State ◽  
Decidability And Complexity

The conventional forbidden state problem for discrete event systems is concerned with the issue of synthesizing a maximally permissive control policy to prevent a discrete event system from reaching any forbidden state during the course of its computation. In this paper, we regard the forbidden state problem as a decision problem, and investigate the decidability/complexity issue of the problem under two new types of control policies, namely, non-blocking and fair policies, for finite state systems and Petri nets.

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