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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Introduction to SYSTEM SCIENCE with MATLAB Explores the mathematical basis for developing and evaluating continuous and discrete systems In this revised Second Edition of Introduction to System Science with MATLAB¯®, the authors Gary Sandquist and Zakary Wilde provide a comprehensive exploration of essential concepts, mathematical framework, analytical resources, and productive skills required to address any rational system confidently and adequately for quantitative evaluation. This Second Edition is supplemented with new updates to the mathematical and technical materials from the first edition. A new chapter to assist readers to generalize and execute algorithms for systems development and analysis, as well as an expansion of the chapter covering specific system science applications, is included. The book provides the mathematical basis for developing and evaluating single and multiple input/output systems that are continuous or discrete. It offers the mathematical basis for the recognition, definition, quantitative modeling, analysis, and evaluation in system science. The book also provides: * A comprehensive introduction to system science and the principles of causality and cause and effect operations, including their historical and scientific background * A complete exploration of fundamental systems concepts and basic system equations, including definitions and classifications * Practical applications and discussions of single-input systems, multiple-input systems, and system modeling and evaluation * An in-depth examination of generalized system analysis methods and specific system science applications Perfect for upper-level undergraduate and graduate students in engineering, mathematics, and physical sciences, Introduction to System Science with MATLAB¯® will also earn a prominent place in libraries of researchers in the life and social sciences.
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Table of Contents
Cover
Title Page
Copyright Page
Preface
1 Introduction
1.1 System Science
1.2 Principle of Causality
1.3 Overview of System Science
1.4 Outline and Utilization of Text
1.5 Summary
Bibliography
Problems
2 Fundamental System Concepts
2.1 Definitions of System Concepts and Terms
2.2 Discussion of System Concepts
2.3 Classification of Systems by Type
2.4 System Analysis and Evaluation Using a Computer
2.5 Summary
Bibliography
Problems
3 Basic System Equations
3.1 Functional Dependence of System Causes and Effects
3.2 Classification of System Equations
3.3 Summary
Bibliography
Problems
4 Single‐Input Systems
4.1 Definition and Significance of a Single‐Input System
4.2 Single‐Input, Single‐Output Systems
4.3 Single‐Input, Multiple‐Output Systems
4.4 Treatment of Single‐Input Systems Using MATLAB Symbolic Toolbox
4.5 Summary
Bibliography
Problems
5 Multiple‐Input Systems
5.1 Definition and Mathematical Significance
5.2 Multiple‐Input, Single‐Output Systems
5.3 Multiple‐Input, Multiple‐Output Systems
5.4 Summary
Bibliography
Problems
6 System Modeling
6.1 Graphical Representation of Systems
6.2 Modeling System Inputs, Outputs, and Kernels
6.3 Paradigm for System Modeling, Analysis, and Evaluation
6.4 Summary
Bibliography
Problems
7 Analysis Methods for Systems with Linear Kernels
7.1 Background and Justification
7.2 Linearization Methods
7.3 Single‐Input Linear Systems
7.4 Multiple‐Input Linear Systems
7.5 Summary
Bibliography
Problems
8 Generalized System Analysis Methods
8.1 Simplification and Reduction of System Kernels
8.2 System Normalization and Parameter Reduction
8.3 Systems with Feedback
8.4 Computer‐Aided Analysis of Systems
8.5 Summary
Bibliography
Problems
9 System Science Applications
9.1 Classification of System Science by Topics
9.2 System Science Applications to Space, Time, Matter, and Energy in Physical Science
9.3 Earth Science Applications of System Science
9.4 Life Systems Applications of System Science
9.5 Applications of System Science to Human Life
9.6 Applications of System Science to Human Society
9.7 Applications of System Science to the Arts
9.8 Applications of System Science to Technology
9.9 Applications of System Science to Religion
9.10 Applications of System Science to History
General System Science Bibliography
10 System Modeling Paradigms
10.1 Background
10.2 Modeling Paradigm
10.3 Essential System Modeling Paradigm Steps
10.4 Example of Analysis Process after System Identification using MATLAB
10.5 Final Words
Bibliography
Index
End User License Agreement
List of Tables
Chapter 1
Table 1‐1 Common Statements with Cause and Effect Consequences
Table 1‐2 Prominent System Scientists in the Twentieth Century
Table 1‐3 Suggested Study Sections and Problem Assignments by Discipline
Chapter 2
Table 2‐1 MATLAB Symbolic Operations for System Modeling
Chapter 3
Table 3‐1 Table of System Equations (Bold
e
and
c
are multi‐valued variabl...
Chapter 4
Table 4‐1 Integrating Factors for System Equations
Table 4‐2 Equivalence Second‐Order Ordinary Differential Equations (ODEs) a...
Table 4‐3 MATLAB Symbolic Operations for System Modeling
Chapter 6
Table 6‐1 Manipulation of Block Diagrams
Table 6‐2 Tabulation Form for System Inputs and Outputs and Kernel Component...
Table 6‐3 International System of Units (SI)
Table 6‐4 Physical Laws and Effects by Scientific Field
Table 6‐5 Major System Modeling Methods
Table 6‐6 Paradigm for a Typical System Study
Chapter 8
Table 8‐1 Kernel Modification Applications
Table 8‐2 Critical Values for System Equations
Table 8‐3 Various Variable Normalization Definitions
Table 8‐4 Minimum Parameter System Equations
Table 8‐5 Feedback Kernel and Effect on System Gain
Chapter 9
Table 9‐1 Classification of System Science Topics
Table 9‐2 Modeling Problems from the Physical Sciences
Table 9‐3 Modeling Problems for the Earth Science Systems
Table 9‐4 Modeling Problems for the Life Sciences
Table 9‐5 Stress Values for Selected Events
Table 9‐5.1 Stress Values for Selected Events
Table 9‐6 Potential Impacts of Stress Levels
Table 9‐7 U.S. Health Care Costs Chained to 2010 Dollars
Table 9‐8 Typical Human Blood Chemistry
Table 9‐9 Human Endocrine Types
Table 9‐10 Modeling Problems for Human Biology
Table 9‐11 Existing Regional Population Model
Table 9‐12 Projected Regional Population Model
Table 9‐13 U.S. Economic Activity, Total Energy Consumption, and Cost
Table 9‐14 Francis Bacon's Classification of Knowledge
Table 9‐15 Francis Bacon’s Model for National Economies
Table 9‐16 Numerical Weighting for Adverbs and Adjectives
Table 9‐17 Fine Arts Models
Table 9‐18 Models for Industrial Systems
Table 9‐19 Models for Philosophy and Religion
Table 9‐20 Major National and International Events
Chapter 10
Table 10‐1 World Wide Web (WWW) Nomenclature Table
List of Illustrations
Chapter 1
Fig. 1‐1 Model for investigating systems.
Chapter 2
Fig. 2‐1 Isolation of a system from its environment.
Fig. 2‐2 Intrinsic or internal system feedback.
Fig. 2‐3 Extrinsic or external system feedback.
Chapter 3
Fig. 3‐1 Discrete and continuous change of a system’s state.
Fig. 3‐2 Canonical block diagram for a system.
Chapter 4
Fig. 4‐1 Comparison of continuous and discrete system responses.
Fig. 4‐2 Simple mass‐spring‐friction vibration system.
Chapter 6
Fig. 6‐1 Basic canonical system block diagram.
Fig. 6‐2 Typical block diagram for a compound system.
Fig. 6‐3 Sample compound block diagram.
Fig. 6‐4 Typical signal‐flow graph.
Fig. 6‐5 Equivalent block diagram and signal‐flow graph.
Fig. 6‐6 Sample organizational diagram for a typical business firm.
Fig. 6‐7 Reduced block diagram for organization diagram in Figure 6-6.
Fig. 6‐8 Monotonic decreasing response.
Fig. 6‐9 Monotonic increasing response.
Fig. 6‐10 Curves of
and
.
Fig. 6‐11 Curves of
and
.
Fig. 6‐12 Curves of
and
.
Fig. 6‐13 Curves of
and
.
Fig. 6‐14 Typical contracting tree diagram.
Fig. 6‐15 Typical expanding tree diagram.
Chapter 8
Fig. 8‐1 General model for population change with time.
Fig. 8‐2 Graph of parameter sensitivity vs. system output.
Fig. 8‐3 Graph of the effect of feedback on the general single‐input, single...
Chapter 9
Fig. 9‐1 Relativistic system model with no feedback.
Fig. 9‐2 Relativistic energy system model with feedback.
Fig. 9‐3 Increase of carbon dioxide in atmosphere.
Fig. 9‐4 Block diagram and model for geothermal energy system.
Fig. 9‐5 Inventories and flow of terrestrial water.
Fig. 9‐6 Terrestrial water exchange model.
Fig. 9‐7 Terrestrial radio‐wave spectrum.
Fig. 9‐8 Density of electrons in Earth’s atmosphere.
Fig. 9‐9 Atmospheric pressure for Mars, Earth, and Venus.
Fig. 9‐10 Atmospheric temperature for Mars, Earth, and Venus.
Fig. 9‐11 System model for lungs.
Fig. 9‐12 Frequency distribution of sunlight and plant leaf absorption. ...
Fig. 9‐13 Circulatory system model schematic.
Fig. 9‐14 Decision tree for medication.
Fig. 9‐15 Block diagram for societal crime cost model.
Fig. 9‐16 Various responses for societal crime cost system.
Fig. 9‐17 Ranking of human values by age.
Fig. 9‐18 Graphical display for decision analysis.
Fig. 9‐19 Model for quantitative evaluation of sentences.
Fig. 9‐20 Linear stability criterion for space‐independent nuclear reactor k...
Fig. 9‐21 Phase space of space independent kinetic equations at high flux.
Fig. 9‐22 Phase plane of stable flux and xenon response at high flux for
γ
...
Fig. 9‐23 Phase plane of unstable flux and xenon response at high flux for
Fig. 9‐24 Phase plane of threshold flux and iodine response at high flux for...
Fig. 9‐25 Phase plane of unstable flux and iodine response at high flux for ...
Fig. 9‐26 Fluid flow model with friction.
Fig. 9‐27 Vehicle flow data.
Fig. 9‐28 Block diagram for automobile traffic model.
Fig. 9‐29 Religion.
Fig. 9‐30 Expansion of aggressive societies.
Chapter 10
Fig. 10‐1 Normalize population change using MATLAB.
Guide
Cover Page
Title Page
Copyright Page
Preface
Table of Contents
Begin Reading
Index
Wiley End User License Agreement
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Introduction to System Science with MATLAB
Second Edition
Gary Marlin Sandquist
and
Zakary Robert Wilde
This second edition first published 2023© 2023 John Wiley & Sons Ltd
Edition HistoryPrentice‐Hall, Inc. (1e, 1985)
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.
The right of Gary Marlin Sandquist and Zakary Robert Wilde to be identified as the authors of this work has been asserted in accordance with law.
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Library of Congress Cataloging‐in‐Publication Data applied forHardback ISBN: 9781119213963
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Preface
Purpose. The purpose of this text in system science is to provide the reader with a comprehensive, rigorous introduction to the recognition, definition, quantitative modeling, approximation, analysis, and evaluation of rational systems. The novel approach to system science developed herein is a fundamental one, based upon the principle of causality. This concept is pursued across all disciplines that are amenable to rational, deterministic logic. The goal of the textbook is to sufficiently develop those essential perceptions and skills within the reader so that the development and analysis of any rational system may be approached with confidence and competence. However, the reader is cautioned that no textbook alone in system science can provide the full resources and level of competence required to master the subject and contribute to the knowledge and understanding of systems in a significant manner.
Prerequisites. The emphasis of this textbook is on quantitative system science, and thus a basic background and skill with mathematics is essential for success. For full mathematical comprehension of all text material, the reader should be familiar with ordinary and partial differential equations and basic definitions and operations with matrices. However, with a basic understanding of ordinary differential equations and perhaps the assistance of a good instructor, the reader should be able to comprehend most material in the book.
Content and Arrangement.Chapter 1 introduces the principle of causality, or cause and effect, which is the basis for understanding quantitative modeling of rational systems. Chapter 2 provides the basic concepts and terms employed in system science. The mathematical formulation of the basic system equations governing any quantitative system is presented in Chapter 3. In Chapter 4 the mathematical treatment of single‐input systems is explored for both continuous and discrete system models. The mathematical methods pertinent to multiple‐input systems are developed in Chapter 5. Chapter 6 presents some of the essential methods required to quantitatively establish and model systems. In Chapter 7 the development and analysis of systems with linear kernels is addressed. Chapter 8 provides some of the important methods for processing and analyzing systems. Specific system science applications are demonstrated for a broad variety of system topics in Chapter 9. Chapter 10 describes paradigms for performing system modeling.
Suggested Course Outlines. The entire text taken in chapter sequence is suitable for two semesters or three quarter courses meeting three to five hours per week. Other reasonable chapter sequences are shown in the following diagram:
A detailed study schedule, appropriate for various disciplines, is given in Section 1.3.2 of Chapter 1. Both reading and applicable problems assignments are provided.
Examples and Exercises. Generally examples are provided to demonstrate each major system concept and method presented. Furthermore, over 750 system problems and exercises of graded difficulty are provided for developing system skills.
Computers and System Science. It is apparent that the digital computer, with its combined capabilities of high speed, great precision, massive data storage, and near universal availability, will have a profound impact upon system science. Even now a system investigator no longer needs to possess nor exercise broad and profound analytical and numerical skills to pursue sophisticated system studies. For the most part, even micro or personal computers have the capacity, speed, and software required to perform surprisingly sophisticated system analysis functions. And in the future, the system investigator will be able to devote major efforts toward accurate modeling and comprehensive evaluation of systems and leave the burdensome numerical tasks to the computer. Chapter 8 presents numerical algorithms in BASIC and FORTRAN for solving multiple‐output system equations.
References. References, pertinent to the material in each chapter, are given at the end of the respective chapters. A rather complete bibliography for each of the major fields of application of system science is given at the end of Chapter 9.
Acknowledgments. The development and production of this book has been realized through the talents and efforts of many people. Former teachers, colleagues, and students have contributed in various ways. Professor R.F. Boehm and the staff in the Department of Mechanical and Industrial Engineering provided the resources and personnel to create the draft text. The staff of John Wiley & Sons have provided the professional effort and support to produce the finished textbook. Finally, I acknowledge my appreciation and love to my wife Kristine and children – Titia, Julia, Taunia, Cynthia, and Carl for permitting me the uninterrupted time necessary.
