scholarly journals Identification of Stochastic Timed Discrete Event Systems with st-IPN

2014 ◽  
Vol 2014 ◽  
pp. 1-21 ◽  
Author(s):  
Doyra Mariela Muñoz ◽  
Antonio Correcher ◽  
Emilio García ◽  
Francisco Morant
Keyword(s):  
Petri Net ◽  
Discrete Event Systems ◽  
Discrete Event ◽  
Input Output ◽  
Identification Process ◽  
Sequence Of Events ◽  
Input And Output ◽  
Event Systems ◽  
Systems Modelling ◽  
Stochastic Time

This paper presents a method for the identification of stochastic timed discrete event systems, based on the analysis of the behavior of the input and output signals, arranged in a timeline. To achieve this goal stochastic timed interpreted Petri nets are defined. These nets link timed discrete event systems modelling with stochastic time modelling. The procedure starts with the observation of the input/output signals; these signals are converted into events, so that the sequence of events is the observed language. This language arrives to an identifier that builds a stochastic timed interpreted Petri net which generates the same language. The identified model is a deterministic generator of the observed language. The identification method also includes an algorithm that determines when the identification process is over.

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.

Fault Detection, Isolation and Characterisation for Discrete Event Systems Based on Petri Nets Models

2010 ◽  
pp. 387-416
Author(s):  
Dimitri Lefebvre ◽  
Edouard Leclercq ◽  
Souleiman Ould El Mehdi
Keyword(s):  
Petri Nets ◽  
Petri Net ◽  
Discrete Event Systems ◽  
Discrete Event ◽  
Practical Interest ◽  
Transportation Systems ◽  
Intermittent Faults ◽  
Event Systems ◽  
Stochastic Time

Petri net models are used to detect and isolate faults in case of discrete event systems as manufacturing, robotic, communication and transportation systems. This chapter addresses two problems. The first one is the structure designs and parameters identification of the Petri net models according to the observation and analysis of the sequences of events that are collected. Deterministic and stochastic time Petri nets are concerned. The proposed method is based on a statistical analysis of data and has a practical interest as long as sequences of events are already saved by supervision systems. The second problem concerns the use of the resulting Petri net models to detect, isolate and characterize faults in discrete event systems. This contribution includes the characterization of intermittent faults. This issue is important because faults are often progressive from intermittent to definitive and early faults detection and isolation improve productivity and save money and resources.

A Simple Petri Net controller in Discrete Event systems

2012 ◽  
Vol 45 (6) ◽  
pp. 188-193 ◽  
Author(s):  
M. Zareiee ◽  
A. Dideban ◽  
A.A. Orouji ◽  
H. Alla
Keyword(s):  
Petri Net ◽  
Discrete Event Systems ◽  
Discrete Event ◽  
Event Systems

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
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