Modeling And Simulation Of Systems Using Matlab And Simulink

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.

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.

Systems engineering encompasses a variety of components that embrace physical and conceptual phenomena. This book addresses all aspects of systems modeling and simulation. The first part of the text presents a step-by-step procedure for modeling different types of systems using techniques like a graph theoretic approach, interpretive structural modeling, and system dynamics modeling. It also covers physical systems framework and identification, systems analysis, and optimization aspects and numerical analysis. The second part presents real-life examples of simulation that illustrate state-of-the-art simulation. The text also develops MATLAB®and Simulink programs for system simulation.

The essential, intermediate and advanced topics of Simulink are covered in the book. The concept of multi-domain physical modeling concept and tools in Simulink are illustrated with examples for engineering systems and multimedia information. The combination of Simulink and numerical optimization methods provides new approaches for solving problems, where solutions are not known otherwise.

This is probably the first book that employs the technique of simulation experiments as a means of reinforcing the basic concepts of communication theory. Undergraduate students are generally exposed to a mathematically rigorous treatment of communications theory but seldom have the benefit of a practical-orientated approach employing modelling and simulation for a thorough assimilation of the subject. This book can supplement any standard textbook to cover this significant lacuna in the existing learning methodology. It uses MATLAB®, the language of the technical computing fraternity, for the purpose. The introductory chapters provide an overview of computer simulation and MATLAB programming concepts. Thereafter, communications concepts are presented in the traditional manner but followed up with appropriate simulations in MATLAB/Simulink®. Relevant MATLAB source code is given whenever it is used to illustrate a point. All the source code given in the text has been tested on MATLAB kernel version 7.10 (Release R2010a) and is provided in the accompanying CD.

In this textbook, the author teaches readers how to model and simulate a unit process operation through developing mathematical model equations, solving model equations manually, and comparing results with those simulated through software. It covers both lumped parameter systems and distributed parameter systems, as well as using MATLAB and Simulink to solve the system model equations for both. Simplified partial differential equations are solved using COMSOL, an effective tool to solve PDE, using the fine element method. This book includes end of chapter problems and worked examples, and summarizes reader goals at the beginning of each chapter.

Mechatronic Systems consist of components and/or sub-systems which are from different engineering domains. For example, a solenoid valve has three domains that work in a synergistic fashion: electrical, magnetic, and mechanical (translation). Over the last few decades, engineering systems have become more and more mechatronic. Automobiles are transforming from being gasoline-powered mechanical devices to electric, hybrid electric and even autonomous. This kind of evolution has been possible through the synergistic integration of technology that is derived from different disciplines. Understanding and designing mechatronic systems needs to be a vital component of today's engineering education. Typical engineering programs, however, mostly continue to train students in academic silos (otherwise known as majors) such as mechanical, electrical, or computer engineering. Some universities have started offering one or more courses on this subject and a few have even started full programs around the theme of Mechatronics. Modeling the behavior of Mechatronic systems is an important step for analysis, synthesis, and optimal design of such systems. One key training necessary for developing this expertise is to have comfort and understanding of the basic physics of different domains. A second need is a suitable software tool that implements these laws with appropriate flexibility and is easy to learn. This short text addresses the two needs: it is written for an audience who will likely have good knowledge and comfort in one of the several domains that we will consider, but not necessarily all; the book will also serve as a guide for the students to learn how to develop mechatronic system models with Simscape (a MATLAB tool box). The book uses many examples from different engineering domains to demonstrate how to develop mechatronic system models and what type of information can be obtained from the analyses.

Dynamic Systems Biology Modeling and Simuation consolidates and unifies classical and contemporary multiscale methodologies for mathematical modeling and computer simulation of dynamic biological systems – from molecular/cellular, organ-system, on up to population levels. The book pedagogy is developed as a well-annotated, systematic tutorial – with clearly spelled-out and unified nomenclature – derived from the author’s own modeling efforts, publications and teaching over half a century. Ambiguities in some concepts and tools are clarified and others are rendered more accessible and practical. The latter include novel qualitative theory and methodologies for recognizing dynamical signatures in data using structural (multicompartmental and network) models and graph theory; and analyzing structural and measurement (data) models for quantification feasibility. The level is basic-to-intermediate, with much emphasis on biomodeling from real biodata, for use in real applications. Introductory coverage of core mathematical concepts such as linear and nonlinear differential and difference equations, Laplace transforms, linear algebra, probability, statistics and stochastics topics; PLUS ....... The pertinent biology, biochemistry, biophysics or pharmacology for modeling are provided, to support understanding the amalgam of “math modeling” with life sciences. Strong emphasis on quantifying as well as building and analyzing biomodels: includes methodology and computational tools for parameter identifiability and sensitivity analysis; parameter estimation from real data; model distinguishability and simplification; and practical bioexperiment design and optimization. Companion website provides solutions and program code for examples and exercises using Matlab, Simulink, VisSim, SimBiology, SAAMII, AMIGO, Copasi and SBML-coded models. A full set of PowerPoint slides are available from the author for teaching from his textbook. He uses them to teach a 10 week quarter upper division course at UCLA, which meets twice a week, so there are 20 lectures. They can easily be augmented or stretched for a 15 week semester course. Importantly, the slides are editable, so they can be readily adapted to a lecturer’s personal style and course content needs. The lectures are based on excerpts from 12 of the first 13 chapters of DSBMS. They are designed to highlight the key course material, as a study guide and structure for students following the full text content. The complete PowerPoint slide package (~25 MB) can be obtained by instructors (or prospective instructors) by emailing the author directly, at: [email protected]