A unique, hands-on guide to interactive modeling and
simulation of engineering systems

This book describes advanced, cutting-edge techniques for
dynamic system simulation using the DESIRE modeling/simulation
software package. It offers detailed guidance on how to implement
the software, providing scientists and engineers with powerful
tools for creating simulation scenarios and experiments for such
dynamic systems as aerospace vehicles, control systems, or
biological systems.

Along with two new chapters on neural networks, Advanced
Dynamic-System Simulation, Second Edition revamps and updates
all the material, clarifying explanations and adding many new
examples. A bundled CD contains an industrial-strength version of
OPEN DESIRE as well as hundreds of program examples that readers
can use in their own experiments. The only book on the market to
demonstrate model replication and Monte Carlo simulation of
real-world engineering systems, this volume:

* Presents a newly revised systematic procedure for
difference-equation modeling

* Covers runtime vector compilation for fast model replication on
a personal computer

* Discusses parameter-influence studies, introducing very fast
vectorized statistics computation

* Highlights Monte Carlo studies of the effects of noise and
manufacturing tolerances for control-system modeling

* Demonstrates fast, compact vector models of neural networks for
control engineering

* Features vectorized programs for fuzzy-set controllers, partial
differential equations, and agro-ecological modeling

Advanced Dynamic-System Simulation, Second Edition is a
truly useful resource for researchers and design engineers in
control and aerospace engineering, ecology, and agricultural
planning. It is also an excellent guide for students using
DESIRE.

GRANINO A. KORN, PhD, is Professor of Electrical and Computer Engineering at the University of Arizona and a partner with G.A. and T.M. Korn Industrial Consultants, a company that designs systems for interactive simulation of dynamic systems and neural networks. He is the author of fifteen books, a Fellow of the IEEE, and the recipient of several awards for his work on computer simulation.

A unique, hands-on guide to interactive modeling and simulation of engineering systems

This book describes advanced, cutting-edge techniques for dynamic system simulation using the DESIRE modeling/simulation software package. It offers detailed guidance on how to implement the software, providing scientists and engineers with powerful tools for creating simulation scenarios and experiments for such dynamic systems as aerospace vehicles, control systems, or biological systems.

Along with two new chapters on neural networks, Advanced Dynamic-System Simulation, Second Edition revamps and updates all the material, clarifying explanations and adding many new examples. A bundled CD contains an industrial-strength version of OPEN DESIRE as well as hundreds of program examples that readers can use in their own experiments. The only book on the market to demonstrate model replication and Monte Carlo simulation of real-world engineering systems, this volume:

• Presents a newly revised systematic procedure for difference-equation modeling
• Covers runtime vector compilation for fast model replication on a personal computer
• Discusses parameter-influence studies, introducing very fast vectorized statistics computation
• Highlights Monte Carlo studies of the effects of noise and manufacturing tolerances for control-system modeling
• Demonstrates fast, compact vector models of neural networks for control engineering
• Features vectorized programs for fuzzy-set controllers, partial differential equations, and agro-ecological modeling

Advanced Dynamic-System Simulation, Second Edition is a truly useful resource for researchers and design engineers in control and aerospace engineering, ecology, and agricultural planning. It is also an excellent guide for students using DESIRE.

PREFACE xiii

CHAPTER 1 DYNAMIC-SYSTEM MODELS AND SIMULATION 1

SIMULATION IS EXPERIMENTATION WITH MODELS 1

1-1 Simulation and Computer Programs 1

1-2 Dynamic-System Models 2

1-3 Experiment Protocols Define Simulation Studies 3

1-4 Simulation Software 4

1-5 Fast Simulation Program for Interactive Modeling 5

ANATOMY OF A SIMULATION RUN 8

1-6 Dynamic-System Time Histories Are Sampled Periodically 8

1-7 Numerical Integration 10

1-8 Sampling Times and Integration Steps 11

1-9 Sorting Defined-Variable Assignments 12

SIMPLE APPLICATION PROGRAMS 12

1-10 Oscillators and Computer Displays 12

1-11 Space-Vehicle Orbit Simulation with Variable-Step Integration 15

1-12 Population-Dynamics Model 17

1-13 Splicing Multiple Simulation Runs: Billiard-Ball Simulation 17

INRODUCTION TO CONTROL-SYSTEM SIMULATION 21

1-14 Electrical Servomechanism with Motor-Field Delay and Saturation 21

1-15 Control-System Frequency Response 23

1-16 Simulation of a Simple Guided Missile 24

STOP AND LOOK 28

1-17 Simulation in the Real World: A Word of Caution 28

References 29

CHAPTER 2 MODELS WITH DIFFERENCE EQUATIONS, LIMITERS, AND SWITCHES 31

SAMPLED-DATA SYSTEMS AND DIFFERENCE EQUATIONS 31

2-1 Sampled-Data Difference-Equation Systems 31

2-2 Solving Systems of First-Order Difference Equations 32

2-3 Models Combining Differential Equations and Sampled-Data Operations 35

2-4 Simple Example 35

2-5 Initializing and Resetting Sampled-Data Variables 35

TWO MIXED CONTINUOUS/SAMPLED-DATA SYSTEMS 37

2-6 Guided Torpedo with Digital Control 37

2-7 Simulation of a Plant with a Digital PID Controller 37

DYNAMIC-SYSTEM MODELS WITH LIMITERS AND SWITCHES 40

2-8 Limiters, Switches, and Comparators 40

2-9 Integration of Switch and Limiter Outputs, Event Prediction, and Display Problems 43

2-10 Using Sampled-Data Assignments 44

2-11 Using the step Operator and Heuristic Integration-Step Control 44

2-12 Example: Simulation of a Bang-Bang Servomechanism 45

2-13 Limiters, Absolute Values, and Maximum/Minimum Selection 46

2-14 Output-Limited Integration 47

2-15 Modeling Signal Quantization 48

EFFICIENT DEVICE MODELS USING RECURSIVE ASSIGNMENTS 48

2-16 Recursive Switching and Limiter Operations 48

2-17 Track/Hold Simulation 49

2-18 Maximum-Value and Minimum-Value Holding 50

2-19 Simple Backlash and Hysteresis Models 51

2-20 Comparator with Hysteresis (Schmitt Trigger) 52

2-21 Signal Generators and Signal Modulation 53

References 55

CHAPTER 3 FAST VECTORMATRIX OPERATIONS AND SUBMODELS 57

ARRAYS, VECTORS, AND MATRICES 57

3-1 Arrays and Subscripted Variables 57

3-2 Vector and Matrices in Experiment Protocols 58

3-3 Time-History Arrays 58

VECTORS AND MODEL REPLICATION 59

3-4 Vector Operations in DYNAMIC Program Segments: The Vectorizing Compiler 59

3-5 MatrixVector Products in Vector Expressions 61

3-6 Index-Shift Operation 63

3-7 Sorting Vector and Subscripted-Variable Assignments 64

3-8 Replication of Dynamic-System Models 64

MORE VECTOR OPERATIONS 65

3-9 Sums, DOT Products, and Vector Norms 65

3-10 Maximum/Minimum Selection and Masking 66

VECTOR EQUIVALENCE DECLARATIONS SIMPLIFY MODELS 67

3-11…