Fishwick P.A. (editor) Handbook of Dynamic System Modeling
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x Contents
25.3 Performance of a Queueing System ................................................................................. 25-4
25.4 Queueing System Dynamics ............................................................................................ 25-6
25.5 Little’s Law ......................................................................................................................... 25-7
25.6 Simple Markovian Queueing Models .............................................................................. 25-8
25.7 Markovian Queueing Networks ....................................................................................... 25-11
25.8 Non-Markovian Queueing Systems ................................................................................. 25-17
26 Port-Based Modeling of Engineering Systems in Terms of Bond Graphs
Peter Breedveld .............................................................................................................................. 26-1
26.1 Introduction ...................................................................................................................... 26-1
26.2 Structured Systems: Physical Components and Interaction .......................................... 26-4
26.3 Bond Graphs ..................................................................................................................... 26-5
26.4 Multiport Generalizations ................................................................................................ 26-21
26.5 Conclusion ........................................................................................................................ 26-28
27 System Dynamics Modeling of Environmental Systems Andrew Ford ................ 27-1
27.1 Introductory Examples ..................................................................................................... 27-1
27.2 Comparison of the Flowers and Sales Models ................................................................ 27-4
27.3 Background on Daisy World ............................................................................................ 27-6
27.4 The Daisy World Model ................................................................................................... 27-6
27.5 The Daisy World Management Flight Simulator ............................................................ 27-9
28 Dynamic Simulation with Energy Systems Language Clay L. Montague ............. 28-1
28.1 Introduction ...................................................................................................................... 28-1
28.2 Reading an Energy Systems Language Diagram ............................................................. 28-4
28.3 Translating a Diagram to Dynamic Equations ................................................................ 28-8
28.4 Calibration of Model Constants ...................................................................................... 28-21
28.5 Preparation for Simulation .............................................................................................. 28-22
28.6 Dynamic Output of the Marsh Sector Model ................................................................. 28-27
28.7 A Brief Comparison with Forrester’s Systems Dynamics Approach .............................. 28-29
28.8 Conclusions ....................................................................................................................... 28-31
29 Ecological Modeling and Simulation: From Historical Development to
Individual-Based Modeling
David R.C. Hill and P. Coquillard ................................... 29-1
29.1 Introduction ...................................................................................................................... 29-1
29.2 An Old Story? .................................................................................................................... 29-2
29.3 Determinism or Probability? ........................................................................................... 29-5
29.4 Modeling Techniques ....................................................................................................... 29-5
29.5 The Use of Models in Ecology ......................................................................................... 29-6
29.6 Models are Scientific Instruments ................................................................................... 29-7
29.7 Levels of Organization and Methodological Choices ..................................................... 29-8
29.8 Individual-Based Models ................................................................................................. 29-9
29.9 Applications ...................................................................................................................... 29-12
29.10 Conclusion ........................................................................................................................ 29-15
30 Ontology-Based Simulation in Agriculture and Natural Resources
Howard Beck, Rohit Badal and Yunchul Jung ............................................................................... 30-1
30.1 Introduction ...................................................................................................................... 30-1
30.2 Ways in Which Ontologies can be Applied to Simulation .............................................. 30-2
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30.3 How to Build an Ontology-Based Simulation— Bioprocessing Example ..................... 30-6
30.4 Tools for Ontology-Based Simulation ............................................................................. 30-10
30.5 Conclusions ....................................................................................................................... 30-12
31 Modeling Human Interaction in Organizational Systems
Stewart Robinson ........................................................................................................................... 31-1
31.1 Introduction ...................................................................................................................... 31-1
31.2 Systems and Human Interaction ..................................................................................... 31-2
31.3 Why Model Human Interaction? ..................................................................................... 31-3
31.4 Modeling Human Interaction: Research and Practice .................................................... 31-4
31.5 The KBI Methodology ...................................................................................................... 31-5
31.6 A Case Study: Modeling Human Decision Making at Ford Motor Company .............. 31-8
31.7 Conclusion ........................................................................................................................ 31-12
32 Military Modeling Roger Smith ........................................................................................ 32-1
32.1 Introduction ...................................................................................................................... 32-1
32.2 Applications ...................................................................................................................... 32-1
32.3 Representation .................................................................................................................. 32-2
32.4 Dynamics .......................................................................................................................... 32-4
32.5 Modeling Approach .......................................................................................................... 32-8
32.6 Military Simulation Systems ............................................................................................ 32-11
32.7 Conclusion ........................................................................................................................ 32-12
33 Dynamic Modeling in Management Science Michael Pidd ..................................... 33-1
33.1 Introduction ...................................................................................................................... 33-1
33.2 An Approach to Dynamic Systems Modeling in Management Science ......................... 33-4
33.3 Discrete Event Simulation ................................................................................................ 33-7
33.4 System Dynamics in Management Science ..................................................................... 33-16
33.5 Model Validation .............................................................................................................. 33-21
33.6 Chapter Summary ............................................................................................................ 33-22
34 Modeling and Analysis of Manufacturing Systems
E. Lefeber and J.E. Rooda .............................................................................................................. 34-1
34.1 Introduction ...................................................................................................................... 34-1
34.2 Preliminaries ..................................................................................................................... 34-2
34.3 Analytical Models for Steady-State Analysis ................................................................... 34-3
34.4 Discrete-Event Models ..................................................................................................... 34-7
34.5 Effective Process Times .................................................................................................... 34-8
34.6 Control of Manufacturing Systems: A Framework ......................................................... 34-10
34.7 Standard Fluid Model and Extensions ............................................................................ 34-12
34.8 Flow Models ...................................................................................................................... 34-16
34.9 Conclusions ....................................................................................................................... 34-18
35 Sensor Network Component-Based Simulator
Boleslaw K. Szymanski and Gilbert Gang Chen ............................................................................ 35-1
35.1 The Need for a New Sensor Network Simulator ............................................................. 35-1
35.2 Component Simulation Toolkit ....................................................................................... 35-3
35.3 Wireless Sensor Network Simulation .............................................................................. 35-7
35.4 Conclusions ....................................................................................................................... 35-15
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V Case Studies
36 Multidomain Modeling with Modelica
Martin Otter, Hilding Elmqvist and Sven Erik Mattsson .............................................................. 36-1
36.1 Modelica Overview ........................................................................................................... 36-1
36.2 Modelica Basics ................................................................................................................. 36-3
36.3 Modelica Libraries ............................................................................................................ 36-17
36.4 Symbolic Processing of Modelica Models ....................................................................... 36-19
36.5 Outlook ............................................................................................................................. 36-25
37 On Simulation of Simulink
®
Models for Model-Based Design
Rohit Shenoy, Brian McKay and Pieter J. Mosterman .................................................................. 37-1
37.1 Introduction ...................................................................................................................... 37-1
37.2 The Case Study Example .................................................................................................. 37-3
37.3 Designing with Simulation .............................................................................................. 37-4
37.4 Obtaining Computational Models .................................................................................. 37-4
37.5 The Robotic Arm Model .................................................................................................. 37-7
37.6 Using Computational Models for Control Design ......................................................... 37-12
37.7 Testing with Model-Based Design ................................................................................... 37-16
37.8 Conclusions ....................................................................................................................... 37-19
Index ........................................................................................................................................................ I-1
Abstract
A dynamic model is a model that describes how a system changes in time. In some cases, time is the
only independent variable, and in others, there are additional variables such as those of spatial frames.
Even though the concept of creating a dynamic model, capturing the dynamics of a system, is ubiquitous,
the topic tends to be splintered across numerous disciplines, from mathematical modeling and computer
simulation to more qualitative models for software design and science. Moreover, models have a variety
of representations from the traditional notations of mathematics to diagrammatic, and even immersive
representations. The purpose of this volume is to provide a text that brings together all of these expressions
for dynamic models.
This book emphasizes presenting a “computer science slant” toward the problems of model design,
representation, and analysis. As such, each chapter will be of a tutorial or survey nature, including
mathematical descriptions, pseudocode, and diagrams wherever possible. The idea is to inform the reader
as to how to use the model(s). A Web page with chapter author links will be provided on the CRC Web
site.
The book is novel for the following key reasons:
•
Most comprehensive books available on the topic of dynamic modeling—there have been many
books on modeling—tend to be particular to a specific community, rather than cutting across
interdisciplinary lines. This book spans numerous disciplines to educate the reader about the wide
variety of modeling methods available for dynamic systems.
•
It provides the readers with pseudocode, diagrams, and methods for representing, simulating, and
analyzing models.
•
It brings together theory, foundations, a catalog of model types, as well as applications that use
them. In this sense, the book can be used as a reference guide or in the classroom as a primary text
or as a secondary reference.
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Intended Audience
This book is meant to be a comprehensive and complete reference guide for dynamic modeling. As such,
we expect a very large audience from core disciplines (mathematics, computer science, and physics) to all
science and engineering disciplines. The applications section will inform readers how to apply modeling
methods to several areas.
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Preface
Dynamic system modeling is defined as creating time-dependent models for physical systems. In particular,
we are concerned with digital computer models rather than scale or analog models for dynamic phenom-
ena. This subject matter can be placed, more broadly, within the overall topic of modeling.Whenwestudy
a system, we build many sorts of models to describe it, including capturing salient system characteristics
of geometry, information, knowledge, and dynamics. Therefore, dynamics is only one type of a model,
but a vital one if we are to represent how a system behaves and changes state over time. Dynamic system
modeling tends to be highly interdisciplinary. So, one is likely to see practitioners belonging to different
areas from computer science and engineering to philosophy and the life sciences. The topic does not fit
into a singular mold.
Another interesting aspect of dynamic modeling is the range of coverage from the very general to the
very specific. One may build models that capture the dynamics over a wide set of domains. Other models
are more targeted toward one specific domain. For example, a model defining the topological character of
a digital circuit is classified within the domain of electrical engineering; however, a bond graph can also
capture the dynamics of the digital circuit using a more general energy-based specification. The reader
may wonder if it is better to be general or specific when modeling. An underlying thesis of this book is
that one must maintain a balanced approach by understanding specific models on the one hand, while
appreciating generalized dynamic knowledge on the other. This approach naturally results in variety in
modeling in which handbooks excel. Model types have different presentations: some are text-based using
symbols while others have associated diagrams. Also, all models have issues involving connectivity—how
to connect components within models at the same level of abstraction, or how to capture multiple levels
of abstraction or aggregation using varying scales.
This handbook is meant to be an aid to readers interested in dynamic models for the purpose of a
quick “lookup” reference or a more in-depth study in the area of dynamic modeling as a discipline. The
book can also be used within the classroom if the goal is to educate students on variety within model
types and the practice of dynamic modeling. The handbook is organized through an introduction to
dynamic models by way of general issues, representations, and philosophy. This introduction is followed
by modeling methodologies defined as approaches to the modeling process. Modeling methodologies
also contain the topic of how to execute models on a computer once those models have been designed.
The “multiobject and system” section addresses the issues of scale, heterogeneity, and composition. The
next section covers specific model types often characterized by specific visual or text-based grammars.
The section on application domains is primarily concerned with models that tend to be tied to a specific
discipline or a set of closely related subdisciplines. The handbook concludes with case studies using two
well-known commercial packages that support dynamic model construction, simulation, and analysis.
I hope that the reader will obtain useful dynamic model types for an application of interest and will
find that the handbook serves in the capacity of a useful reference whenever it is necessary to consider how
systems function, and are represented, over time and space.
Paul A. Fishwick
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Editor
Paul A. Fishwick is professor of Computer and Information Science and Engineering at the Univer-
sity of Florida. He received his BS in Mathematics from the Pennsylvania State University, MS in Applied
Science from the College of William and Mary, and PhD in Computer and Information Science from the
University of Pennsylvania in 1986. He has six years of industrial/government production and research
experience working at Newport News Shipbuilding and Dry Dock Co. (doing CAD/CAM parts definition
research) and at NASA Langley Research Center (studying engineering database models for structural
engineering). His research interests are computer simulation modeling and analysis methods for complex
systems. He is a Senior Member of the IEEE and a Fellow of the Society for Computer Simulation. He
is also a member of the IEEE Society for Systems, Man and Cybernetics; ACM; and AAAI. Dr. Fishwick
founded the comp.simulation Internet news group (Simulation Digest) in 1987, which has served numer-
ous subscribers. He has chaired several workshops and conferences in the area of computer simulation,
including General Chair of the 2000 Winter Simulation Conference. He was chairman of the IEEE Com-
puter Society Technical Committee on Simulation (TCSIM) for two years (1988–1990) and has served
on the editorial boards of several journals including the ACM Transactions on Modeling and Computer
Simulation; IEEE Transactions on Systems, Man and Cybernetics; Transactions of the Society for Computer
Simulation; International Journal of Computer Simulation; and Journal of Systems Engineering. He has
delivered 12 international keynote addresses at major conferences relating to simulation. He has published
over 180 technical papers, authored one textbook, coedited two Springer-Verlag volumes in modeling and
simulation, and published 12 book chapters. His recent book Aesthetic Computing was published in April
2006 by MIT Press.
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