Modeling and Simulation of Systems Using MATLAB and Simulink: 1st Edition (Hardback) book cover

Modeling and Simulation of Systems Using MATLAB and Simulink

1st Edition

By Devendra K. Chaturvedi

CRC Press

734 pages | 603 B/W Illus.

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Hardback: 9781439806722
pub: 2009-12-16
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Not only do modeling and simulation help provide a better understanding of how real-world systems function, they also enable us to predict system behavior before a system is actually built and analyze systems accurately under varying operating conditions. Modeling and Simulation of Systems Using MATLAB® and Simulink® provides comprehensive, state-of-the-art coverage of all the important aspects of modeling and simulating both physical and conceptual systems. Various real-life examples show how simulation plays a key role in understanding real-world systems. The author also explains how to effectively use MATLAB and Simulink software to successfully apply the modeling and simulation techniques presented.

After introducing the underlying philosophy of systems, the book offers step-by-step procedures for modeling different types of systems using modeling techniques, such as the graph-theoretic approach, interpretive structural modeling, and system dynamics modeling. It then explores how simulation evolved from pre-computer days into the current science of today. The text also presents modern soft computing techniques, including artificial neural networks, fuzzy systems, and genetic algorithms, for modeling and simulating complex and nonlinear systems. The final chapter addresses discrete systems modeling.

Preparing both undergraduate and graduate students for advanced modeling and simulation courses, this text helps them carry out effective simulation studies. In addition, graduate students should be able to comprehend and conduct simulation research after completing this book.

Table of Contents

Introduction to Systems


Classification of Systems

Linear Systems

Time-Varying vs. Time-Invariant Systems

Lumped vs. Distributed Parameter Systems

Continuous- and Discrete-Time Systems

Deterministic vs. Stochastic Systems

Hard and Soft Systems

Analysis of Systems

Synthesis of Systems

Introduction to System Philosophy

System Thinking

Large and Complex Applied System Engineering: A Generic Modeling

Systems Modeling


Need of System Modeling

Modeling Methods for Complex Systems

Classification of Models

Characteristics of Models


Mathematical Modeling of Physical Systems

Formulation of State Space Model of Systems

Physical Systems Theory

System Components and Interconnections

Computation of Parameters of a Component

Single Port and Multiport Systems

Techniques of System Analysis

Basics of Linear Graph Theoretic Approach

Formulation of System Model for Conceptual System

Formulation System Model for Physical Systems

Topological Restrictions

Development of State Model of Degenerative System

Solution of State Equations




Liapunov Stability

Performance Characteristics of Linear Time Invariant Systems

Formulation of State Space Model Using Computer Program (SYSMO)

Model Order Reduction


Difference between Model Simplification and Model Order Reduction

Need for Model Order Reduction

Principle of Model Order Reduction

Methods of Model Order Reduction

Applications of Reduced-Order Models

Analogous of Linear Systems


Force–Voltage (f–v) Analogy

Force–Current (f–i) Analogy

Interpretive Structural Modeling


Graph Theory

Interpretive Structural Modeling

System Dynamics Techniques


System Dynamics of Managerial and Socioeconomic System

Traditional Management

Sources of Information

Strength of System Dynamics

Experimental Approach to System Analysis

System Dynamics Technique

Structure of a System Dynamic Model

Basic Structure of System Dynamics Models

Different Types of Equations Used in System Dynamics Techniques

Symbol Used in Flow Diagrams

Dynamo Equations

Modeling and Simulation of Parachute Deceleration Device

Modeling of Heat Generated in a Parachute during Deployment

Modeling of Stanchion System of Aircraft Arrester Barrier System



Advantages of Simulation

When to Use Simulations

Simulation Provides

How Simulations Improve Analysis and Decision Making

Applications of Simulation

Numerical Methods for Simulation

The Characteristics of Numerical Methods

Comparison of Different Numerical Methods

Errors during Simulation with Numerical Methods

Nonlinear and Chaotic Systems


Linear vs. Nonlinear System

Types of Nonlinearities

Nonlinearities in Flight Control of Aircraft


Introduction to Chaotic System

Historical Prospective

First-Order Continuous-Time System


Second-Order System

Third-Order System

Modeling with Artificial Neural Network


Artificial Neural Networks

Modeling Using Fuzzy Systems


Fuzzy Sets

Features of Fuzzy Sets

Operations on Fuzzy Sets

Characteristics of Fuzzy Sets

Properties of Fuzzy Sets

Fuzzy Cartesian Product

Fuzzy Relation

Approximate Reasoning

Defuzzification Methods

Introduction to Fuzzy Rule–Based Systems

Applications of Fuzzy Systems to System Modeling

Takagi–Sugeno–Kang Fuzzy Models

Adaptive Neuro-Fuzzy Inferencing Systems

Steady State DC Machine Model

Transient Model of a DC Machine

Fuzzy System Applications for Operations Research

Discrete-Event Modeling and Simulation


Some Important Definitions

Queuing System

Discrete-Event System Simulation

Components of Discrete-Event System Simulation

Input Data Modeling

Family of Distributions for Input Data

Random Number Generation

Chi-Square Test

Kolomogrov–Smirnov Test

Appendix A: MATLAB

Appendix B: Simulink

Appendix C: Glossary


About the Author

Devendra K. Chaturvedi is a professor in the Department of Electrical Engineering at Dayalbagh Educational Institute in India.

Subject Categories

BISAC Subject Codes/Headings:
TECHNOLOGY & ENGINEERING / Engineering (General)