Numerical computing with Simulink: 1 Creating simulations
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| Format: | Buch |
| Sprache: | English |
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Philadelphia, PA
SIAM, Society for Industrial and Applied Mathematics
2007
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| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXI, 306 S. Ill., graph. Darst. |
| ISBN: | 9780898716375 |
Internformat
MARC
| LEADER | 00000nam a2200000 cc4500 | ||
|---|---|---|---|
| 001 | BV023220711 | ||
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| 008 | 080318s2007 xxuad|| |||| 00||| eng d | ||
| 020 | |a 9780898716375 |9 978-0-898716-37-5 | ||
| 035 | |a (OCoLC)612678683 | ||
| 035 | |a (DE-599)BVBBV023220711 | ||
| 040 | |a DE-604 |b ger |e rakwb | ||
| 041 | 0 | |a eng | |
| 044 | |a xxu |c US | ||
| 049 | |a DE-29T |a DE-11 | ||
| 100 | 1 | |a Gran, Richard J. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Numerical computing with Simulink |n 1 |p Creating simulations |c Richard J. Gran |
| 264 | 1 | |a Philadelphia, PA |b SIAM, Society for Industrial and Applied Mathematics |c 2007 | |
| 300 | |a XXI, 306 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 0 | 7 | |a Numerische Mathematik |0 (DE-588)4042805-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Datenverarbeitung |0 (DE-588)4011152-0 |2 gnd |9 rswk-swf |
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| 689 | 0 | 0 | |a Datenverarbeitung |0 (DE-588)4011152-0 |D s |
| 689 | 0 | 1 | |a Numerische Mathematik |0 (DE-588)4042805-9 |D s |
| 689 | 0 | 2 | |a SIMULINK |0 (DE-588)4480546-9 |D s |
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-016406617 | |
Datensatz im Suchindex
| _version_ | 1807954214774636544 |
|---|---|
| adam_text |
Contents
List of Figures
xi
List of Tables
xvii
Preface
xix
1
Introduction to Simulink
1
1.1
Using a Picture to Write a Program
. 1
1.2
Example
1:
Galileo Drops Two Objects from the Leaning Tower of Pisa
. 5
1.3
Example
2:
Modeling a Pendulum and the Escapement of a Clock
. 17
1.3.1
History of Pendulum Clocks
. 18
1.3.2
A Simulation Model for the Clock
. 20
1.4
Example
3:
Complex Rotations
—
The
Foucault
Pendulum
. 24
1.4.1
Forces from Rotations
. 25
1.4.2
Foucault
Pendulum Dynamics
. 26
1.5
Further Reading
. 31
Exercises
.· . 32
2
Linear Differential Equations, Matrix Algebra, and Control Systems
33
2.1
Linear Differential Equations: Linear Algebra
. 33
2.1.1
Solving a Differential Equation at Discrete Time Steps
. 36
2.1.2
Linear Differential Equations in Simulink
. 38
2.2
Laplace Transforms for Linear Differential Equations
. 40
2.3
Linear Feedback Control
. 43
2.3.1
What Is a Control System?
. 44
2.3.2
Control Systems and Linear Differential Equations
. 48
2.4
Linearization and the Control of Linear Systems
. 49
2.4.1
Linearization
. 49
2.4.2
Eigenvalues and the Response of a Linear System
. 51
2.5
Poles and the Roots ()f the Characteristic Polynomial
. 55
2.5.1
Feedback of the Position of the Mass in the Spring-Mass Model
· · 56
2.5.2
Feedback of the Velocity of the Mass in the Spring-Mass Model
. · 57
2.5.3
Comparing Position and Rate Feedback
. 61
2.5.4
The Structure of a Control System: Transfer Functions
. 62
vii
Contents
2.6
Transfer
Functions: Bode Plots
. 64
2.6.1
The Bode Plot for Continuous Time
Systems
. 65
2.6.2
Calculating the Bode Plot for Continuous Time Systems
. 65
2.7
PD Control,
PID
Control, and Full State Feedback
. 69
2.7.1
PD Control
. 69
2.7.2 PID
Control
. 71
2.7.3
Full State Feedback
. 72
2.7.4
Getting Derivatives for
PID
Control or Full State Feedback
. 74
2.8
Further Reading
. 78
Exercises
. 78
Nonlinear Differential Equations
81
3.1
The
Lorenz Attractor. 81
3.1.1
Linear Operating Points: Why the
Lorenz
Attractor Is Chaotic
. 83
3.2
Differential Equation Solvers in
MATLAB
and Simulink
. 86
3.3
Tables, Interpolation, and Curve Fitting in Simulink
. 87
3.3.1
The Simple Lookup Table
. 88
3.3.2
Interpolation: Fitting a Polynomial to the Data and Using the Result
in Simulink
. 91
3.3.3
Using Real Data in the Model: From Workspace and File
. 92
3.4
Rotations in Three Dimensions:
Euler
Rotations, Axis-Angle
Representations, Direction Cosines, and the Quaternion
. 94
3.4.1
Euler
angles
. 95
3.4.2
Direction Cosines
. 98
3.4.3
Axis-Angle Rotations
. 99
3.4.4
The Quaternion Representation
. 99
3.5
Modeling the Motion of a Satellite in Orbit
. 105
3.5.1
Creating an Attitude Error When Using Direction Cosines
. 107
3.5.2
Creating an Attitude Error Using Quaternion Representations
. 109
3.5.3
The Complete Spacecraft Model
. 109
3.6
Further Reading
. 112
Exercises
. 112
Digital Signal Processing in Simulink
115
4.1
Difference Equations, Fibonacci Numbers, and z-Transforms
. 116
4.1.1
The z-Transform
. 119
4.1.2
Fibonacci (Again) Using z-Transforms
. 120
4.2
Digital Sequences, Digital Filters, and Signal Processing
. 121
4.2.1
Digital Filters, Using z-Transforms, and Discrete Transfer Functions
121
4.2.2
Simulink Experiments: Filtering a Sinusoidal Signal and Aliasing
. 123
4.2.3
The Simulink Digital Library
. 128
4.3
Matrix Algebra and Discrete Systems
. 130
4.4
The Bode Plot for Discrete Time Systems
. . 135
4.5
Digital Filter Design: Sampling Analog Signals, the Sampling Theorem,
and Filters
. . 136
4.5.1
Sampling and Reconstructing Analog Signals
. . 137
Contents ix
4.5.2 Analog
Prototypes
of
Digital Filters: The Butterworth Filter . 142
4.6 The Signal Processing Blockset.145
4.6.1
Fundamentals of the
Signal Processing Blockset: Analog Filters . . 146
4.6.2
Creating
Digital Filters
from
Analog Filters. 148
4.6.3 Digital Signal Processing. 149
4.6.4
Implementing
Digital Filters:
Structures
and Limited
Precision
. . . 153
4.6.5
Batch Filtering Operations,
Buffers, and Frames. 160
4.7
The Phase-Locked Loop.
165
4.8
Further Reading
. 170
Exercises
. 171
5
Random Numbers, White Noise, and Stochastic Processes
173
5.1
Modeling with Random Variables in Simulink: Monte Carlo Simulations
. 173
5.1.1
Monte Carlo Analysis and the Central Limit Theorem
.174
5.1.2
Simulating a Rayleigh Distributed Random Variable
.176
5.2
Stochastic Processes and White Noise
.177
5.2.1
The Random Walk Process
.178
5.2.2
Brownian Motion and White Noise
.180
5.3
Simulating a System with White Noise Inputs Using the Weiner Process
. 184
5.3.1
White Noise and a Spring-Mass-Damper System
.184
5.3.2
Noisy Continuous and Discrete Time Systems:
The Covariance Matrix
.186
5.3.3
Discrete Time Equivalent of a Continuous Stochastic Process
. 189
5.3.4
Modeling a Specified Power Spectral Density:
1//
Noise
.194
5.4
Further Reading
.199
Exercises
.199
6
Modeling a Partial Differential Equation in Simulink
201
6.1
The Heat Equation: Partial Differential Equations in Simulink
.202
6.1.1
Finite Dimensional Models
.202
6.1.2
An Electrical Analogy of the Heat Equation
.203
6.2
Converting the Finite Model into Equations for Simulation with Simulink
205
6.2.1
Using
Kirchhoff
's
Law to Get the Equations
.206
6.2.2
The State-Space Model
.208
6.3
Partial Differential Equations for Vibration
.212
6.4
Further Reading
.212
Exercises
.213
7
Stateflow: A Tool for Creating and Coding State Diagrams, Complex Logic,
Event Driven Actions, and Finite State Machines
215
7.1
Properties of Stateflow: Building a Simple Model
.216
7.1.1
Statellow Semantics
.218
7.1.2
Making the Simple Statetlow Chart Do Something
.221
7.1.3
Following Stateflow's Semantics Using the Debugger
.223
7.2
Using Statellow: A Controller for Home Heating
.225
7.2.1
Creating a Model of the System and an Executable Specification
. .225
x
Contents
7.2.2
Stateflow's Action
Language Types
.229
7.2.3
The Heating Controller Layout
.230
7.2.4
Adding the User Actions, the Digital Clock, and the Stateflow Chart
to the Simulink Model of the Home Heating System
.231
7.2.5
Some Comments on Creating the GUI
.239
7.3
Further Reading
.240
Exercise
.240
8
Physical Modeling: SimPowerSystems and SimMechanics
241
8.1
SimPowerSystems
.242
8.1.1
How the SimPowerSystems
Blockset
Works: Modeling a Nonlinear
Resistor
.246
8.1.2
Using the Nonlinear Resistor Block
.248
8.2
Modeling an Electric Train Moving on a Rail
.251
8.3
SimMechanics: A Tool for Modeling Mechanical Linkages
and Mechanical Systems
.256
8.3.1
Modeling a Pendulum with SimMechanics
.257
8.3.2
Modeling the Clock: Simulink and SimMechanics Together
. 260
8.4
More Complex Models in SimMechanics and SimPowerSystems
.262
8.5
Further Reading
.265
Exercises
.267
9
Putting Everything Together: Using Simulink in a System Design Process
269
9.1
Specifications Development and Capture
.270
9.1.1
Modeling and Analysis: Converting the Specifications into an "Ex¬
ecutable Specification"
.271
9.2
Modeling the System to Incorporate the Specifications: Lunar Module
Rotation Using Time Optimal Control
.272
9.2.1
From Specification to Control Algorithm
.273
9.3
Design of System Components to Meet Specifications: Modify the Design
to Accommodate Computer Limitations
.276
9.3.1
Final Lunar Module Control System Executable Specification
. . .279
9.3.2
The Control System Logic: Using Stateflow
.283
9.4
Verification and Validation of the Design
.285
9.5
The Final Step: Creating Embedded Code
.286
9.6
Further Reading
.287
10
Conclusion: Thoughts about Broad-Based Knowledge
289
Bibliography
291
Index
295 |
| adam_txt |
Contents
List of Figures
xi
List of Tables
xvii
Preface
xix
1
Introduction to Simulink
1
1.1
Using a Picture to Write a Program
. 1
1.2
Example
1:
Galileo Drops Two Objects from the Leaning Tower of Pisa
. 5
1.3
Example
2:
Modeling a Pendulum and the Escapement of a Clock
. 17
1.3.1
History of Pendulum Clocks
. 18
1.3.2
A Simulation Model for the Clock
. 20
1.4
Example
3:
Complex Rotations
—
The
Foucault
Pendulum
. 24
1.4.1
Forces from Rotations
. 25
1.4.2
Foucault
Pendulum Dynamics
. 26
1.5
Further Reading
. 31
Exercises
.· . 32
2
Linear Differential Equations, Matrix Algebra, and Control Systems
33
2.1
Linear Differential Equations: Linear Algebra
. 33
2.1.1
Solving a Differential Equation at Discrete Time Steps
. 36
2.1.2
Linear Differential Equations in Simulink
. 38
2.2
Laplace Transforms for Linear Differential Equations
. 40
2.3
Linear Feedback Control
. 43
2.3.1
What Is a Control System?
. 44
2.3.2
Control Systems and Linear Differential Equations
. 48
2.4
Linearization and the Control of Linear Systems
. 49
2.4.1
Linearization
. 49
2.4.2
Eigenvalues and the Response of a Linear System
. 51
2.5
Poles and the Roots ()f the Characteristic Polynomial
. 55
2.5.1
Feedback of the Position of the Mass in the Spring-Mass Model
· · 56
2.5.2
Feedback of the Velocity of the Mass in the Spring-Mass Model
. · 57
2.5.3
Comparing Position and Rate Feedback
. 61
2.5.4
The Structure of a Control System: Transfer Functions
. 62
vii
Contents
2.6
Transfer
Functions: Bode Plots
. 64
2.6.1
The Bode Plot for Continuous Time
Systems
. 65
2.6.2
Calculating the Bode Plot for Continuous Time Systems
. 65
2.7
PD Control,
PID
Control, and Full State Feedback
. 69
2.7.1
PD Control
. 69
2.7.2 PID
Control
. 71
2.7.3
Full State Feedback
. 72
2.7.4
Getting Derivatives for
PID
Control or Full State Feedback
. 74
2.8
Further Reading
. 78
Exercises
. 78
Nonlinear Differential Equations
81
3.1
The
Lorenz Attractor. 81
3.1.1
Linear Operating Points: Why the
Lorenz
Attractor Is Chaotic
. 83
3.2
Differential Equation Solvers in
MATLAB
and Simulink
. 86
3.3
Tables, Interpolation, and Curve Fitting in Simulink
. 87
3.3.1
The Simple Lookup Table
. 88
3.3.2
Interpolation: Fitting a Polynomial to the Data and Using the Result
in Simulink
. 91
3.3.3
Using Real Data in the Model: From Workspace and File
. 92
3.4
Rotations in Three Dimensions:
Euler
Rotations, Axis-Angle
Representations, Direction Cosines, and the Quaternion
. 94
3.4.1
Euler
angles
. 95
3.4.2
Direction Cosines
. 98
3.4.3
Axis-Angle Rotations
. 99
3.4.4
The Quaternion Representation
. 99
3.5
Modeling the Motion of a Satellite in Orbit
. 105
3.5.1
Creating an Attitude Error When Using Direction Cosines
. 107
3.5.2
Creating an Attitude Error Using Quaternion Representations
. 109
3.5.3
The Complete Spacecraft Model
. 109
3.6
Further Reading
. 112
Exercises
. 112
Digital Signal Processing in Simulink
115
4.1
Difference Equations, Fibonacci Numbers, and z-Transforms
. 116
4.1.1
The z-Transform
. 119
4.1.2
Fibonacci (Again) Using z-Transforms
. 120
4.2
Digital Sequences, Digital Filters, and Signal Processing
. 121
4.2.1
Digital Filters, Using z-Transforms, and Discrete Transfer Functions
121
4.2.2
Simulink Experiments: Filtering a Sinusoidal Signal and Aliasing
. 123
4.2.3
The Simulink Digital Library
. 128
4.3
Matrix Algebra and Discrete Systems
. 130
4.4
The Bode Plot for Discrete Time Systems
. . 135
4.5
Digital Filter Design: Sampling Analog Signals, the Sampling Theorem,
and Filters
. . 136
4.5.1
Sampling and Reconstructing Analog Signals
. . 137
Contents ix
4.5.2 Analog
Prototypes
of
Digital Filters: The Butterworth Filter . 142
4.6 The Signal Processing Blockset.145
4.6.1
Fundamentals of the
Signal Processing Blockset: Analog Filters . . 146
4.6.2
Creating
Digital Filters
from
Analog Filters. 148
4.6.3 Digital Signal Processing. 149
4.6.4
Implementing
Digital Filters:
Structures
and Limited
Precision
. . . 153
4.6.5
Batch Filtering Operations,
Buffers, and Frames. 160
4.7
The Phase-Locked Loop.
165
4.8
Further Reading
. 170
Exercises
. 171
5
Random Numbers, White Noise, and Stochastic Processes
173
5.1
Modeling with Random Variables in Simulink: Monte Carlo Simulations
. 173
5.1.1
Monte Carlo Analysis and the Central Limit Theorem
.174
5.1.2
Simulating a Rayleigh Distributed Random Variable
.176
5.2
Stochastic Processes and White Noise
.177
5.2.1
The Random Walk Process
.178
5.2.2
Brownian Motion and White Noise
.180
5.3
Simulating a System with White Noise Inputs Using the Weiner Process
. 184
5.3.1
White Noise and a Spring-Mass-Damper System
.184
5.3.2
Noisy Continuous and Discrete Time Systems:
The Covariance Matrix
.186
5.3.3
Discrete Time Equivalent of a Continuous Stochastic Process
. 189
5.3.4
Modeling a Specified Power Spectral Density:
1//
Noise
.194
5.4
Further Reading
.199
Exercises
.199
6
Modeling a Partial Differential Equation in Simulink
201
6.1
The Heat Equation: Partial Differential Equations in Simulink
.202
6.1.1
Finite Dimensional Models
.202
6.1.2
An Electrical Analogy of the Heat Equation
.203
6.2
Converting the Finite Model into Equations for Simulation with Simulink
205
6.2.1
Using
Kirchhoff
's
Law to Get the Equations
.206
6.2.2
The State-Space Model
.208
6.3
Partial Differential Equations for Vibration
.212
6.4
Further Reading
.212
Exercises
.213
7
Stateflow: A Tool for Creating and Coding State Diagrams, Complex Logic,
Event Driven Actions, and Finite State Machines
215
7.1
Properties of Stateflow: Building a Simple Model
.216
7.1.1
Statellow Semantics
.218
7.1.2
Making the Simple Statetlow Chart Do Something
.221
7.1.3
Following Stateflow's Semantics Using the Debugger
.223
7.2
Using Statellow: A Controller for Home Heating
.225
7.2.1
Creating a Model of the System and an Executable Specification
. .225
x
Contents
7.2.2
Stateflow's Action
Language Types
.229
7.2.3
The Heating Controller Layout
.230
7.2.4
Adding the User Actions, the Digital Clock, and the Stateflow Chart
to the Simulink Model of the Home Heating System
.231
7.2.5
Some Comments on Creating the GUI
.239
7.3
Further Reading
.240
Exercise
.240
8
Physical Modeling: SimPowerSystems and SimMechanics
241
8.1
SimPowerSystems
.242
8.1.1
How the SimPowerSystems
Blockset
Works: Modeling a Nonlinear
Resistor
.246
8.1.2
Using the Nonlinear Resistor Block
.248
8.2
Modeling an Electric Train Moving on a Rail
.251
8.3
SimMechanics: A Tool for Modeling Mechanical Linkages
and Mechanical Systems
.256
8.3.1
Modeling a Pendulum with SimMechanics
.257
8.3.2
Modeling the Clock: Simulink and SimMechanics Together
. 260
8.4
More Complex Models in SimMechanics and SimPowerSystems
.262
8.5
Further Reading
.265
Exercises
.267
9
Putting Everything Together: Using Simulink in a System Design Process
269
9.1
Specifications Development and Capture
.270
9.1.1
Modeling and Analysis: Converting the Specifications into an "Ex¬
ecutable Specification"
.271
9.2
Modeling the System to Incorporate the Specifications: Lunar Module
Rotation Using Time Optimal Control
.272
9.2.1
From Specification to Control Algorithm
.273
9.3
Design of System Components to Meet Specifications: Modify the Design
to Accommodate Computer Limitations
.276
9.3.1
Final Lunar Module Control System Executable Specification
. . .279
9.3.2
The Control System Logic: Using Stateflow
.283
9.4
Verification and Validation of the Design
.285
9.5
The Final Step: Creating Embedded Code
.286
9.6
Further Reading
.287
10
Conclusion: Thoughts about Broad-Based Knowledge
289
Bibliography
291
Index
295 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Gran, Richard J. |
| author_facet | Gran, Richard J. |
| author_role | aut |
| author_sort | Gran, Richard J. |
| author_variant | r j g rj rjg |
| building | Verbundindex |
| bvnumber | BV023220711 |
| ctrlnum | (OCoLC)612678683 (DE-599)BVBBV023220711 |
| format | Book |
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| id | DE-604.BV023220711 |
| illustrated | Illustrated |
| index_date | 2024-07-02T20:15:56Z |
| indexdate | 2024-08-21T00:18:19Z |
| institution | BVB |
| isbn | 9780898716375 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016406617 |
| oclc_num | 612678683 |
| open_access_boolean | |
| owner | DE-29T DE-11 |
| owner_facet | DE-29T DE-11 |
| physical | XXI, 306 S. Ill., graph. Darst. |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | SIAM, Society for Industrial and Applied Mathematics |
| record_format | marc |
| spelling | Gran, Richard J. Verfasser aut Numerical computing with Simulink 1 Creating simulations Richard J. Gran Philadelphia, PA SIAM, Society for Industrial and Applied Mathematics 2007 XXI, 306 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Numerische Mathematik (DE-588)4042805-9 gnd rswk-swf Datenverarbeitung (DE-588)4011152-0 gnd rswk-swf SIMULINK (DE-588)4480546-9 gnd rswk-swf Datenverarbeitung (DE-588)4011152-0 s Numerische Mathematik (DE-588)4042805-9 s SIMULINK (DE-588)4480546-9 s DE-604 (DE-604)BV023220691 1 Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016406617&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Gran, Richard J. Numerical computing with Simulink Numerische Mathematik (DE-588)4042805-9 gnd Datenverarbeitung (DE-588)4011152-0 gnd SIMULINK (DE-588)4480546-9 gnd |
| subject_GND | (DE-588)4042805-9 (DE-588)4011152-0 (DE-588)4480546-9 |
| title | Numerical computing with Simulink |
| title_auth | Numerical computing with Simulink |
| title_exact_search | Numerical computing with Simulink |
| title_exact_search_txtP | Numerical computing with Simulink |
| title_full | Numerical computing with Simulink 1 Creating simulations Richard J. Gran |
| title_fullStr | Numerical computing with Simulink 1 Creating simulations Richard J. Gran |
| title_full_unstemmed | Numerical computing with Simulink 1 Creating simulations Richard J. Gran |
| title_short | Numerical computing with Simulink |
| title_sort | numerical computing with simulink creating simulations |
| topic | Numerische Mathematik (DE-588)4042805-9 gnd Datenverarbeitung (DE-588)4011152-0 gnd SIMULINK (DE-588)4480546-9 gnd |
| topic_facet | Numerische Mathematik Datenverarbeitung SIMULINK |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016406617&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV023220691 |
| work_keys_str_mv | AT granrichardj numericalcomputingwithsimulink1 |