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Kaliczyńska Małgorzata - Automation 2017: innovations in automations, robotics and measurement techniques

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Kaliczyńska Małgorzata Automation 2017: innovations in automations, robotics and measurement techniques

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Control and Automation
Springer International Publishing AG 2017
Roman Szewczyk , Cezary Zieliski and Magorzata Kaliczyska (eds.) Automation 2017 Advances in Intelligent Systems and Computing 10.1007/978-3-319-54042-9_1
Petri Nets in Discrete-Event and Hybrid Systems Modelling, Analysing, Performance Evaluation and Control
Frantiek apkovi 1
(1)
Institute of Informatics, Slovak Academy of Sciences, Dbravsk cesta 9, 845 07 Bratislava, Slovak Republic
Frantiek apkovi
Email:
URL: http://www.ui.sav.sk/home/capkovic/capkhome.htm
Abstract
Place/transition Petri nets, timed Petri nets (here time expresses the duration of separate operations) are used here in order to model, analyse, evaluate performance, and control discrete-event systems. Typical representatives of discrete-event systems are flexible manufacturing systems, transport systems, communication systems, etc. Hybrid Petri nets, more precisely first-order hybrid Petri nets, are used here in order to model, analyse and control hybrid systems. Typical representatives of hybrid systems are manufacturing systems in general - industrial production systems. The systems in question usually consist of cooperating subsystems (modules, agents). Particular approaches are illustrated on four case studies.
F. apkoviPartially supported by the Slovak Grant Agency for Science VEGA under grant # 2/0029/17.
Introduction and Preliminaries
Petri nets (PN) in general represent the effective tool for modelling discrete event systems (DES) and hybrid systems (HS). DES are systems behaviour of which depends on an occurrency of discrete events, i.e. they are discrete in nature. HS consists of both discrete variables and continuous ones.
1.1 Place/Transition Petri Nets
Place/transition PN (P/T PN) [] of FMS. As to their structure P/T PN are bipartite directed graphs Automation 2017 innovations in automations robotics and measurement techniques - image 1 . The nodes are represented by places Automation 2017 innovations in automations robotics and measurement techniques - image 2 , and transitions Automation 2017 innovations in automations robotics and measurement techniques - image 3 . Two kinds of edges (from places to transitions and the edges from transitions to places) are given, respectively, in the form of the sets Automation 2017 innovations in automations robotics and measurement techniques - image 4 and Automation 2017 innovations in automations robotics and measurement techniques - image 5 . Next to the structure, P/T PN have also their dynamics which can formally be expressed as Automation 2017 innovations in automations robotics and measurement techniques - image 6 . Here, X is the set of the state vectors Picture 7 of the places ( Automation 2017 innovations in automations robotics and measurement techniques - image 8 symbolizes integers), U is the set of the state vectors Automation 2017 innovations in automations robotics and measurement techniques - image 9 of the transitions, Automation 2017 innovations in automations robotics and measurement techniques - image 10 is a transition function yielding the new state (marking) vector Picture 11 based on both an existing state Automation 2017 innovations in automations robotics and measurement techniques - image 12 and an occurrence of discrete events Automation 2017 innovations in automations robotics and measurement techniques - image 13 . Dynamics, being the evolution of marking of the P/T PN places, is given by the linear discrete model Automation 2017 innovations in automations robotics and measurement techniques - image 14 restricted by the inequality Automation 2017 innovations in automations robotics and measurement techniques - image 15 , Automation 2017 innovations in automations robotics and measurement techniques - image 16 . Here, Automation 2017 innovations in automations robotics and measurement techniques - image 17 with Automation 2017 innovations in automations robotics and measurement techniques - image 18 (i.e. Picture 19 , where Automation 2017 innovations in automations robotics and measurement techniques - image 20 symbolizes natural numbers), is the marking vector expressing the state of the marking of the particular places (the number of tokens inside the places) and Automation 2017 innovations in automations robotics and measurement techniques - image 21 with Automation 2017 innovations in automations robotics and measurement techniques - image 22 is the vector of the states of transitions (either disabled or enabled). The matrix Automation 2017 innovations in automations robotics and measurement techniques - image 23 , Picture 24 , expresses the PN structure. Picture 25 ( Picture 26 ), (here Picture 27 symbolizes non-negative integers) and Picture 28 ( Picture 29 ) are the incidence matrices of the arcs corresponding, respectively, to the sets F and G .
The places model activities (operations) in FMS, while the transitions model the discrete events (starting/ending the activities). P/T PN do not depend on time. Their transitions, places, arcs and tokens do not contain any time specifications.
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