ABSTRACT

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.

    chapter 1|30 pages

    Introduction to Systems

    chapter 2|72 pages

    Systems Modeling

    chapter 3|115 pages

    Formulation of State Space Model of Systems

    chapter 4|57 pages

    Model Order Reduction

    chapter 5|24 pages

    Analogous of Linear Systems

    chapter 6|26 pages

    Interpretive Structural Modeling

    chapter 7|73 pages

    System Dynamics Techniques

    chapter 8|32 pages

    Simulation

    chapter 9|69 pages

    Nonlinear and Chaotic System

    chapter 10|24 pages

    Modeling with Artificial Neural Network

    chapter 11|77 pages

    Modeling Using Fuzzy Systems

    chapter 12|15 pages

    Discrete-Event Modeling and Simulation