4.4.2 Net-Centric Dynamic System Model Architecture

2004 ◽  
Vol 14 (1) ◽  
pp. 774-786
Author(s):  
Yves LaCerte
Keyword(s):  
Dynamic System ◽  
System Model ◽  
Dynamic System Model

scholarly journals MODEL DINAMIS SISTEM KETERSEDIAAN DAGING SAPI NASIONAL

2011 ◽  
Vol 12 (1) ◽  
pp. 128 ◽  
Author(s):  
Harmini Harmini ◽  
Ratna Winandi Asmarantaka ◽  
Juniar Atmakusuma
Keyword(s):  
Computer Program ◽  
Dynamic System ◽  
Artificial Insemination ◽  
System Model ◽  
Percentage Error ◽  
National Program ◽  
Cross Breeding ◽  
Self Sufficiency ◽  
Innovative Solution ◽  
Dynamic System Model

The purpose of this paper is to assess whether the national program on beef self sufficiency could be achieved at 2014. A dynamic system model with Vensim computer program is applied. The model validated by Mean Absolute Percentage Error. The results shows high accuracies of the model. The assessment show that, first, the beef self sufficiency would not be achieved at 2014 if the program are treated and running as usual (Scenario I). Second, the beef self sufficiency would be achieved at 2015 if government increase the cow population by reducing the slaughter of local cows and expanding the cross breeding program through artificial insemination (Scenario II). Third, the beef self sufficiency would not be achieved at 2014 if the actual beef consumption are higher than the supply that produce through Scenario II (Scenario III). Another innovative solution for increasing local cow population is needed.

A dynamic system model of testosterone transport and metabolism in normal man

1974 ◽  
Vol 2 (3) ◽  
pp. 307-320 ◽  
Author(s):  
Marlene T. Mayekawa ◽  
Joseph J. DiStefano ◽  
Ronald S. Swerdloff
Keyword(s):  
Dynamic System ◽  
System Model ◽  
Normal Man ◽  
Dynamic System Model

scholarly journals From Verified Parameter Identification to the Design of Interval Observers and Cooperativity-Preserving Controllers

2020 ◽  
Vol 24 (3) ◽  
pp. 509-537
Author(s):  
Andreas Rauh ◽  
Julia Kersten
Keyword(s):  
Parameter Identification ◽  
Dynamic System ◽  
System Model ◽  
Feedback Controllers ◽  
Identification Schemes ◽  
Scale Test ◽  
Verified Bounds ◽  
The University ◽  
Interval Observers ◽  
Dynamic System Model

One of the most important advantages of interval observers is their capability to provide estimates for a given dynamic system model in terms of guaranteed state bounds which are compatible with measured data that are subject to bounded uncertainty. However, the inevitable requirement for being able to produce such verified bounds is the knowledge about a dynamic system model in which possible uncertainties and inaccuracies are themselves represented by guaranteed bounds. For that reason, classical point-valued parameter identification schemes are often not sufficient or should, at least, be handled with sufficient care if safety critical applications are of interest. This paper provides an application-oriented description of the major steps leading from a control-oriented system model with an associated verified parameter identification to a verified design of interval observers which provide the basis for the development and implementation of cooperativity-preserving feedback controllers. The corresponding computational steps are described and visualized for the temperature control of a laboratory-scale test rig available at the Chair of Mechatronics at the University of Rostock.

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