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.

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

scholarly journals MODELING PREDICTIVE TRACKING CONTROL FOR MAX-PLUS LINEAR SYSTEMS IN MANUFACTURING

2020 ◽  
Vol 3 (2) ◽  
pp. 133-147
Author(s):  
Lathifatul Aulia ◽  
Widowati Widowati ◽  
R. Heru Tjahjana ◽  
Sutrisno Sutrisno
Keyword(s):  
Linear Systems ◽  
Production System ◽  
Tracking Control ◽  
Discrete Event Systems ◽  
Discrete Event ◽  
Process Flow ◽  
Sequence Of Events ◽  
Input And Output ◽  
Event System ◽  
Event Systems

Discrete event systems, also known as DES, are class of system that can be applied to systems having an event that occurred instantaneously and may change the state. It can also be said that a discrete event system occurs under certain conditions for a certain period because of the network that describes the process flow or sequence of events. Discrete event systems belong to class of nonlinear systems in classical algebra. Based on this situation, it is necessary to do some treatments, one of which is linearization process. In the other hand, a Max-Plus Linear system is known as a system that produces linear models. This system is a development of a discrete event system that contains synchronization when it is modeled in Max-Plus Algebra. This paper discusses the production system model in manufacturing industries where the model pays the attention into the process flow or sequence of events at each time step. In particular, Model Predictive Control (MPC) is a popular control design method used in many fields including manufacturing systems. MPC for Max-Plus-Linear Systems is used here as the approach that can be used to model the optimal input and output sequences of discrete event systems. The main advantage of MPC is its ability to provide certain constraints on the input and output control signals. While deciding the optimal control value, a cost criterion is minimized by determining the optimal time in the production system that modeled as a Max-Plus Linear (MPL) system. A numerical experiment is performed in the end of this paper for tracking control purposes of a production system. The results were good that is the controlled system showed a good performance.

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 Equivalent and Efficient Optimization Models for an Industrial Discrete Event System with Alternative Structural Configurations

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Juan-Ignacio Latorre-Biel ◽  
Emilio Jiménez-Macías ◽  
Mercedes Pérez de la Parte
Keyword(s):  
Petri Nets ◽  
Petri Net ◽  
Discrete Event Systems ◽  
Discrete Event ◽  
Discrete Event System ◽  
Optimization Techniques ◽  
Event System ◽  
Event Systems ◽  
Structural Configurations ◽  
Computational Resources

Discrete event systems in applications, such as industry and supply chain, may show a very complex behavior. For this reason, their design and operation may be carried out by the application of optimization techniques for decision making in order to obtain their highest performance. In a general approach, it is possible to implement these optimization techniques by means of the simulation of a Petri net model, which may require an intensive use of computational resources. One key factor in the computational cost of simulation-based optimization is the size of the model of the system; hence, it may be useful to apply techniques to reduce it. This paper analyzes the relationship between two Petri net formalisms, currently used in the design of discrete event systems, where it is usual to count on a set of alternative structural configurations. These formalisms are a particular type of parametric Petri nets, called compound Petri nets, and a set of alternative Petri nets. The development of equivalent models under these formalisms and the formal proof of this equivalence are the main topics of the paper. The basis for this formal approach is the graph of reachable markings, a powerful tool able to represent the behavior of a discrete event system and, hence, to show the equivalence between two different Petri net models. One immediate application of this equivalence is the substitution of a large model of a system by a more compact one, whose simulation may be less demanding in the use of computational resources.

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.

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