Multiresolution Signal and System Analysis and the Analysis and Control of Discrete Event Dynamic Systems.

1996 ◽  
Author(s):  
Alan S. Willsky
Keyword(s):  
Dynamic Systems ◽  
System Analysis ◽  
Discrete Event ◽  
Discrete Event Dynamic Systems ◽  
Event Dynamic ◽  
And Control

scholarly journals Modelling and Control of Discrete Event Dynamic Systems

2000 ◽  
Vol 7 (26) ◽  
Author(s):  
Frantisek Capkovic
Keyword(s):  
Petri Nets ◽  
Dynamic Systems ◽  
Discrete Event ◽  
Analytical Models ◽  
Control Synthesis ◽  
Discrete Event Dynamic Systems ◽  
Oriented Graphs ◽  
Knowledge Based ◽  
Event Dynamic ◽  
And Control

Discrete event dynamic systems (DEDS) in general are <br />investigated as to their analytical models most suitable for control<br />purposes and as to the analytical methods of the control synthesis.<br /> The possibility of utilising both the selected kind of Petri nets<br />and the oriented graphs on this way is pointed out. Because many<br />times the control task specifications (like criteria, constraints, <br />special demands, etc.) are given only verbally or in another form of<br />non analytical terms, a suitable knowledge representation about<br />the specifications is needed. Special kinds of Petri nets (logical,<br />fuzzy) are suitable on this way too. Hence, the knowledge-based<br />control synthesis of DEDS can also be examined. The developed<br />graphical tools for model drawing and testing as well as for the<br />automated knowledge-based control synthesis are described and<br />illustratively presented.<br />Two approaches to modelling and control synthesis based on<br />oriented graphs are developed. They are suitable when the <br />system model is described by the special kind of Petri nets - state<br />machines. At the control synthesis the first of them is straightforward<br /> while the second one combines both the straight-lined model<br />dynamics development (starting from the given initial state <br />towards the prescribed terminal one) and the backtracking model<br />dynamics development.

How to model planning and scheduling problems using constraint networks on timelines

2010 ◽  
Vol 25 (3) ◽  
pp. 319-336 ◽  
Author(s):  
Gérard Verfaillie ◽  
Cédric Pralet ◽  
Michel Lemaître
Keyword(s):  
Dynamic Systems ◽  
Discrete Event ◽  
Discrete Event Dynamic Systems ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Constraint Networks ◽  
Modeling Power ◽  
Mission Management ◽  
Event Dynamic ◽  
Domain Management

AbstractThe CNT framework (Constraint Network on Timelines) has been designed to model discrete event dynamic systems and the properties one knows, one wants to verify, or one wants to enforce on them. In this article, after a reminder about the CNT framework, we show its modeling power and its ability to support various modeling styles, coming from the planning, scheduling, and constraint programming communities. We do that by producing and comparing various models of two mission management problems in the aerospace domain: management of a team of unmanned air vehicles and of an Earth observing satellite.

Frameworks for evaluating discrete event dynamic systems

1993 ◽  
Vol 3 (2-3) ◽  
pp. 113-118 ◽  
Author(s):  
Bernard P. Zeigler ◽  
William H. Sanders
Keyword(s):  
Dynamic Systems ◽  
Discrete Event ◽  
Discrete Event Dynamic Systems ◽  
Event Dynamic
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