计算机辅助建模技术

作者简介

《计算机辅助建模技术(影印版)》内容简介：计算机辅助建模技术一书从概念到程序上阐述了从基础系统到高级复杂系统中基于Matlab语言的仿真模拟技术。《计算机辅助建模技术(影印版)》包含计算机辅助建模的设计介绍、物理系统建模仿真、计算机仿真建模实例、高级仿真以及仿真结果的方法性描述等内容，使用了大量的Matlab实例。《计算机辅助建模技术(影印版)》对从事系统仿真领域的相关人员有很好的参考价值。

书籍目录

Preface1.Introduction to System Simulations1.1  Introduction  1.1.1  Model Design  1.1.2  Model Execution  1.1.3  Model Analysis through Outputs1.2  Dynamic System Modeling  1.2.I  Classification of Dynamic Systems1.3  Basic System Elements  1.3.1  Elements in Electrical Systems  1.3.2  Resistor  1.3.3  Capacitor  1.3.4  Inductor1.4  Elements in Mechanical Systems  1.4.1  Springs  1.4.2  Viscous Damper  1.4.3  Mass  1.4.4  Torque-Angular Velocity on a Spring  1.4.5  Viscous Damper  1.4.6  Inertia  1.4.7  Gear Train1.5  Laplace Transform1.6  Combined Elements  1.6.1  Example 1: RLC Circuit  1.6.2  Example 2: Spring， Mass and Damper System  1.6.3  Example 3: Electrical Network1.7  Nonlinear Elements1.8  Thermal and Chemical Systems  1.8.1  Thermal Systems  1.8.2  Chemical Systems1.9  Hydraulic SystemsI.10  Other FormulasReferences2.Creating Your Simulation Environment2.1 Hardware and Software  2.1.1  Hardware for Installing Matlab  2.1.2  Features of Matlab Software2.2  Matlab Basics  2.2.1  Getting Help  2.2.2  Variables  2.2.3  Assignment Statement  2.2.4  Special Variables  2.2.5  Commands Involving Variables  2.2.6  Matrices  2.2.7  Matrix Operations  2.2.8  Matrix Properties  2.2.9  Programming: Flow Control Structures  2.2.10  Flow Control and Loops  2.2.11  Elementary Functions2.3  Basics on Computer Simulations  2.3.I  Creating Data Files  2.3.2  Write Data on a File  2.3.3  Loading a Data File  2.3.4  Deleting Rows and Columns  2.3.5  Long Command Lines  2.3.6  Vectorization  2.3.7  Making Your Own Functions2.4  Memory Management in Simulations2.5  Customized Functions2.6  Computer Simulations with Other LanguagesReferences3.Data Visualization3.1  Elementary X-Y Graphs  3.1.1  Two-Dimensional Graphs  3.1 .2  Multiple Plots and Curves  3.1.3  Polynomials  3.1.4  Plotting Complex Numbers  3.1.5  Axis Scaling  3.1.6  Polar Plots  3.1.7  Discrete Sequence Plot  3.1.8  Multiple Graphs3.2  Elementary X-Y-Z Graphs  3.2.1  Three-Dimensional Basic Plots  3.2.2  Three-Dimensional Color Plots  3.2.3  Discrete Sequence Plot  3.2.4  Polar Plots  3.2.5  Creating Surfaces  3.2.6  Multiple Axes for Different Scaling  3.2.7  Titles with Symbols  3.2.8  Special Graphs  3.2.9  Lines as Ribbons  3.2.10  Contour Plot3.3  Other Software ToolsReferences4.Examples of Different Systems4.1  Chaotic System I : Lorenz Attractor4.2  Chaotic System 2: The Henon-Map4.3  Two-link Robot Manipulator4.4  Nonlinear Systems: State Portrait4.5  Mechanical Systems: Two Mass-spring Cart System4.6  Electrical Systems: L-R-C Circuits4.7  Electro-Mechanical Systems: Magnetically Suspended Ball4.8  Nonlinear Systems: Pendulum4.9  Pneumatic Artificial Muscles （PAM）4.10  Duffing'sEquation4.11  Two-Mass Flexible Rod4.12  Mobile Robot ModelReferences5.Systems Identification and Modeling5.1  System Identification  5.1.I  Introduction  5.1.2  Steps of System Identification  5.1.3  System Identification in Matlab5.2  System Modeling  5.2.1  Systems Control Approaches  5.2.2  DC Motor Controller  5.2.3  Further Analysis on Magnetically Suspended Ball  5.2.4  Inverted Pendulum  5.2.5  Pneumatic Muscle ArmReferences6.System Integration6.1  Integration of Components6.2  Matlab Simulink6.3  Basic Simulations6.4  Data Capturing6.5  Analysis in the S-domain6.6  State Space Models6.7  Integration of Logical Blocks6.8  Integration of Electrical ElementsReferences7.Advanced Simulations7.1  Introduction7.2  Genetic Algorithms  7.2.I  Biological Analogy  7.2.2  Algorithm  7.2.3  Binary Encoding  7.2.4  Selection  7.2.5  Genetic Operators  7.2.6  Example I7.3  Genetic Algorithm Based Cable Selection  7.3.1  Background  7.3.2  Cable Selection"  7.3.3  Genetic Algorithm Based Cable Selection7.4  Advanced Implementation Tools  7.4.I  Calling Built in Function in Command Line  7.4.2  Using the Genetic Algorithm Tool7.5  Additionl Examples  7.5.I  Rastrigin's Function  7.5.2  Schwefel's Function  7.5.3  Griewangk's FunctionReferences8.Modeling of Complex Systems8.1  Complex Systems8.2  Case Study8.3  Neural Network Model  8.3.1  General Framework for ANN Model  8.3.2  Modeling Generator Loads8.4  Data and System Training  8.4.1  Training Model 2  8.4.2  Model 2 Performance8.5  Maximizing Power Generation8.6  Power and Energy Calculations8.7  Remarks  8.7.1  Economical Benefits  8.7.2  Soft Computing ApproachesReferences9.Selecting The Right Software Tool9.1  Scientific Software Tools and Matlab Toolboxes9.2  Image Processing Based Application  9.2.i  Introduction  9.2.2  System Development  9.2.3  Image Analysis  9.2.4  First Reasoning Criterion  9.2.5  Second Reasoning Criterion  9.2.6  How to Use Criteria？  9.2.7  Detection of Illumination Level Variation  9.2.8  Image Enhancement9.3  Setting Up the System  9.3.1  Setup Program 1  9.3.2  Setup Program 2  9.3.3  White Reference Program9.4  Image Acquisition and Processing  9.4.1  Acquisition Algorithm  9.4.2  Image Processing （Main） Algorithm9.5  Experimental Results  9.5.1  Intensity Variation  9.5.2  Object IdentificationReferences10.Exercises10.i  Matrices10.2  Graphics10.3  Analytical Solutions10.4  Transformations10.5  Modeling and ForecastingIndex

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