Dynamic Systems

The major topics covered in this text include mathematical modeling, system-response analysis, and an introduction to feedback control systems.

Dynamic Systems

Craig Kluever ‘s Dynamic Systems: Modeling, Simulation, and Control highlights essential topics such as analysis, design, and control of physical engineering systems, often composed of interacting mechanical, electrical and fluid subsystem components. The major topics covered in this text include mathematical modeling, system-response analysis, and an introduction to feedback control systems. Dynamic Systems integrates an early introduction to numerical simulation using MATLAB®’s Simulink for integrated systems. Simulink® and MATLAB® tutorials for both software programs will also be provided. The author’s text also has a strong emphasis on real-world case studies.

Modeling and Analysis of Dynamic Systems

This text is intended for a first course in dynamic systems and is designed for use by sophomore and junior majors in all fields of engineering, but principally mechanical and electrical engineers.

Modeling and Analysis of Dynamic Systems

This text is intended for a first course in dynamic systems and is designed for use by sophomore and junior majors in all fields of engineering, but principally mechanical and electrical engineers. All engineers must understand how dynamic systems work and what responses can be expected from various physical systems.

Modeling Dynamic Economic Systems

This book explores the dynamic processes in economic systems, concentrating on the extraction and use of the natural resources required to meet economic needs.

Modeling Dynamic Economic Systems

This book explores the dynamic processes in economic systems, concentrating on the extraction and use of the natural resources required to meet economic needs. Sections cover methods for dynamic modeling in economics, microeconomic models of firms, modeling optimal use of both nonrenewable and renewable resources, and chaos in economic models. This book does not require a substantial background in mathematics or computer science.

Modeling Dynamic Systems

This book provides a set of materials that enables educators at the secondary and college levels to teach a one-semester or one-year course in System Dynamics modeling.

Modeling Dynamic Systems

This book provides a set of materials that enables educators at the secondary and college levels to teach a one-semester or one-year course in System Dynamics modeling. These materials are also useful for trainers in a business environment. Developed for beginning modelers, the lessons contained in this book and accompanying CD can be used for a core curriculum or for independent study. The package also includes STELLA® Systems Thinking software from isee systems. Using STELLA, students are actively engaged in the creation of visual models to study and explore a wide variety of problems where the study of the behavior of dynamic systems is the focus.

Handbook of Dynamic System Modeling

Moreover, the models have a variety of representations, from traditional mathematical notations to diagrammatic and immersive depictions. Collecting all of these expressions of dynamic models, the Handbook of Dynamic Sy

Handbook of Dynamic System Modeling

The topic of dynamic models tends to be splintered across various disciplines, making it difficult to uniformly study the subject. Moreover, the models have a variety of representations, from traditional mathematical notations to diagrammatic and immersive depictions. Collecting all of these expressions of dynamic models, the Handbook of Dynamic System Modeling explores a panoply of different types of modeling methods available for dynamical systems. Featuring an interdisciplinary, balanced approach, the handbook focuses on both generalized dynamic knowledge and specific models. It first introduces the general concepts, representations, and philosophy of dynamic models, followed by a section on modeling methodologies that explains how to portray designed models on a computer. After addressing scale, heterogeneity, and composition issues, the book covers specific model types that are often characterized by specific visual- or text-based grammars. It concludes with case studies that employ two well-known commercial packages to construct, simulate, and analyze dynamic models. A complete guide to the fundamentals, types, and applications of dynamic models, this handbook shows how systems function and are represented over time and space and illustrates how to select a particular model based on a specific area of interest.

Dynamic Systems Biology Modeling and Simulation

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.

Dynamic Systems Biology Modeling and Simulation

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]

The Art of Modeling Dynamic Systems

In the coverage of dynamics, there is a definite gap between ``picture-book'' popularizations and the technical literature. This work fills that gap.

The Art of Modeling Dynamic Systems

In the coverage of dynamics, there is a definite gap between ``picture-book'' popularizations and the technical literature. This work fills that gap. Shows engineers and scientists how, by the application of statistical methods, coordinate transformations and mathematical analysis, any complex, unpredictable dynamical system can be mapped--transformed into a simpler, predictable system. The various modeling tools available, their benefits and their limitations are described. Examples and analogies are used in place of theorems and proofs, making this an immediately practical book. By showing how to make models more meaningful and useful, it will be particularly helpful in clearing up the impasse between economics and system dynamics. Features a number of carefully selected references to more mathematical treatments, examples of some of the more specialized techniques and case histories of some models.

Modeling and Identification of Dynamic Systems Exercises

This book contains examples and exercises with modeling problems together with complete solutions. The contents is tailored to the book Ljung-Glad: Modeling and Identification of Dynamic Systems (Studentlitteratur, 2016).

Modeling and Identification of Dynamic Systems   Exercises

This book contains examples and exercises with modeling problems together with complete solutions. The contents is tailored to the book Ljung-Glad: Modeling and Identification of Dynamic Systems (Studentlitteratur, 2016). The exercises are of different levels of difficulty and cover general modeling principles (such as bond graphs) as well as practical tools like Modelica and Simscape. System identification, model and signal properties are also covered together with basic techniques for simulation. Most of the problems deal with issues from industrial applications, but also economic, social and medical cases are covered. The text requires certain knowledge in linear algebra, signal and systems and basic familiarity with physics and statistics. The computer exercises assume access to basic software such as Matlab and Simulink, and to some extent Modelica/Dymola/Simscape. The book is suitable for Master level courses in engineering, but also for practicing engineers.

Fractional order Modeling and Control of Dynamic Systems

This book reports on an outstanding research devoted to modeling and control of dynamic systems using fractional-order calculus.

Fractional order Modeling and Control of Dynamic Systems

This book reports on an outstanding research devoted to modeling and control of dynamic systems using fractional-order calculus. It describes the development of model-based control design methods for systems described by fractional dynamic models. More than 300 years had passed since Newton and Leibniz developed a set of mathematical tools we now know as calculus. Ever since then the idea of non-integer derivatives and integrals, universally referred to as fractional calculus, has been of interest to many researchers. However, due to various issues, the usage of fractional-order models in real-life applications was limited. Advances in modern computer science made it possible to apply efficient numerical methods to the computation of fractional derivatives and integrals. This book describes novel methods developed by the author for fractional modeling and control, together with their successful application in real-world process control scenarios.

Modeling of Dynamic Systems

Written by a recognized authority in the field of identification and control, this book draws together into a single volume the important aspects of system identification AND physical modelling.

Modeling of Dynamic Systems

Written by a recognized authority in the field of identification and control, this book draws together into a single volume the important aspects of system identification AND physical modelling. KEY TOPICS: Explores techniques used to construct mathematical models of systems based on knowledge from physics, chemistry, biology, etc. (e.g., techniques with so called bond-graphs, as well those which use computer algebra for the modeling work). Explains system identification techniques used to infer knowledge about the behavior of dynamic systems based on observations of the various input and output signals that are available for measurement. Shows how both types of techniques need to be applied in any given practical modeling situation. Considers applications, primarily simulation. For practicing engineers who are faced with problems of modeling.

Introduction to Dynamic Systems

Difference and differential equations; Linear algebra; Linear state equations; Linear systems with constant coefficients; Positive systems; Markov chains; Concepts of control; Analysis of nonlinear systems; Some important dynamic systems; ...

Introduction to Dynamic Systems

Difference and differential equations; Linear algebra; Linear state equations; Linear systems with constant coefficients; Positive systems; Markov chains; Concepts of control; Analysis of nonlinear systems; Some important dynamic systems; Optimal control.

Modeling of Dynamic Systems with Engineering Applications

It focuses on the model development of engineering problems rather than response analysis and simulation once a model is available, though these are also covered.

Modeling of Dynamic Systems with Engineering Applications

MODELING OF DYNAMIC SYSTEMS takes a unique, up-to-date approach to systems dynamics and related controls coverage for undergraduate students and practicing engineers. It focuses on the model development of engineering problems rather than response analysis and simulation once a model is available, though these are also covered. Linear graphing and bond graph approaches are both discussed, and computational tools are integrated thoughout. Electrical, mechanical, fluid, and thermal domains are covered, as are problems of multiple domains (mixed systems); the unified and integrated approaches taken are rapidly becoming the standard in the modeling of mechatronic engineering systems.

Modelling and Parameter Estimation of Dynamic Systems

This book presents a detailed examination of the estimation techniques and problems in dynamic systems.

Modelling and Parameter Estimation of Dynamic Systems

This book presents a detailed examination of the estimation techniques and problems in dynamic systems. Containing several illustrations and computer programs, the book promotes a better understanding of system modelling and parameter estimation. Parameter estimation involves observation of a dynamic system to develop mathematical models that represent the system dynamics. With the increasing use of high speed digital computers, elegant and innovative techniques like filter error method, H° and artificial neural networks are finding more and more use in parameter estimation problems. The material is presented in an accessible manner and enables the user to implement and execute the programs and, therefore, gain first-hand experience of the estimation progress.

Understanding Dynamic Systems

Covers lumped network models of systems and their behavior, equivalence and superposition in linear networks, frequency response models, and coupling devices

Understanding Dynamic Systems

Covers lumped network models of systems and their behavior, equivalence and superposition in linear networks, frequency response models, and coupling devices

Modeling and Analysis of Dynamic Systems Second Edition

Modeling and Analysis of Dynamic Systems, Second Edition introduces MATLAB®, Simulink®, and SimscapeTM and then uses them throughout the text to perform symbolic, graphical, numerical, and simulation tasks.

Modeling and Analysis of Dynamic Systems  Second Edition

Modeling and Analysis of Dynamic Systems, Second Edition introduces MATLAB®, Simulink®, and SimscapeTM and then uses them throughout the text to perform symbolic, graphical, numerical, and simulation tasks. Written for junior or senior level courses, the textbook meticulously covers techniques for modeling dynamic systems, methods of response analysis, and provides an introduction to vibration and control systems. These features combine to provide students with a thorough knowledge of the mathematical modeling and analysis of dynamic systems. See What’s New in the Second Edition: Coverage of modeling and analysis of dynamic systems ranging from mechanical to thermal using Simscape Utilization of Simulink for linearization as well as simulation of nonlinear dynamic systems Integration of Simscape into Simulink for control system analysis and design Each topic covered includes at least one example, giving students better comprehension of the subject matter. More complex topics are accompanied by multiple, painstakingly worked-out examples. Each section of each chapter is followed by several exercises so that students can immediately apply the ideas just learned. End-of-chapter review exercises help in learning how a combination of different ideas can be used to analyze a problem. This second edition of a bestselling textbook fully integrates the MATLAB Simscape Toolbox and covers the usage of Simulink for new purposes. It gives students better insight into the involvement of actual physical components rather than their mathematical representations.

Dynamic Modeling of Environmental Systems

After an introduction to the basics of dynamic modeling, the book leads students through an analysis of several environmental problems, including surface-water pollution, matter-cycling disruptions, and global warming.

Dynamic Modeling of Environmental Systems

A primer on modeling concepts and applications that is specifically geared toward the environmental field. Sections on modeling terminology, the uses of models, the model-building process, and the interpretation of output provide the foundation for detailed applications. After an introduction to the basics of dynamic modeling, the book leads students through an analysis of several environmental problems, including surface-water pollution, matter-cycling disruptions, and global warming. The scientific and technical context is provided for each problem, and the methods for analyzing and designing appropriate modeling approaches is provided. While the mathematical content does not exceed the level of a first-semester calculus course, the book gives students all of the background, examples, and practice exercises needed both to use and understand environmental modeling. It is suitable for upper-level undergraduate and beginning-graduate level environmental professionals seeking an introduction to modeling in their field.

Matlab and Simulink Modeling Dynamic Systems

Simulink(R) is a block diagram environment for multidomain simulation and Model-Based Design.

Matlab and Simulink  Modeling Dynamic Systems

Simulink(r) is a block diagram environment for multidomain simulation and Model-Based Design. It supports system-level design, simulation, automatic code generation, and continuous test and verification of embedded systems. Simulink provides a graphical editor, customizable block libraries, and solvers for modeling and simulating dynamic systems. It is integrated with MATLAB(r), enabling you to incorporate MATLAB algorithms into models and export simulation results to MATLAB for further analysis.. The next features are very impiortant in SIMULINK: * Graphical editor for building and managing hierarchical block diagrams * Libraries of predefined blocks for modeling continuous-time and discrete-time systems * Simulation engine with fixed-step and variable-step ODE solvers * Scopes and data displays for viewing simulation results * Project and data management tools for managing model files and data * Model analysis tools for refining model architecture and increasing simulation speed * MATLAB Function block for importing MATLAB algorithms into models * Legacy Code Tool for importing C and C++ code into models

Modeling Identification and Simulation of Dynamical Systems

This book gives an in-depth introduction to the areas of modeling, identification, simulation, and optimization.

Modeling  Identification and Simulation of Dynamical Systems

This book gives an in-depth introduction to the areas of modeling, identification, simulation, and optimization. These scientific topics play an increasingly dominant part in many engineering areas such as electrotechnology, mechanical engineering, aerospace, and physics. This book represents a unique and concise treatment of the mutual interactions among these topics. Techniques for solving general nonlinear optimization problems as they arise in identification and many synthesis and design methods are detailed. The main points in deriving mathematical models via prior knowledge concerning the physics describing a system are emphasized. Several chapters discuss the identification of black-box models. Simulation is introduced as a numerical tool for calculating time responses of almost any mathematical model. The last chapter covers optimization, a generally applicable tool for formulating and solving many engineering problems.

Dynamic Modeling

The book uses STELLA software to develop simulation models, thus allowing readers to convert their understanding of a phenomenon to a computer model, and then run it to yield the inevitable dynamic consequences built into the structure.

Dynamic Modeling

The book uses STELLA software to develop simulation models, thus allowing readers to convert their understanding of a phenomenon to a computer model, and then run it to yield the inevitable dynamic consequences built into the structure. Part I provides an introduction to modeling dynamic systems, while Part II offers general modeling methods. Parts III through VIII then apply these methods to model real-world phenomena from chemistry, genetics, ecology, economics, and engineering. A clear, approachable introduction to the modeling process, of interest in any field where real problems can be illuminated by computer simulation.

Dynamic System Reliability

Offers timely and comprehensive coverage of dynamic system reliability theory This book focuses on hot issues of dynamic system reliability, systematically introducing the reliability modeling and analysis methods for systems with imperfect ...

Dynamic System Reliability

Offers timely and comprehensive coverage of dynamic system reliability theory This book focuses on hot issues of dynamic system reliability, systematically introducing the reliability modeling and analysis methods for systems with imperfect fault coverage, systems with function dependence, systems subject to deterministic or probabilistic common-cause failures, systems subject to deterministic or probabilistic competing failures, and dynamic standby sparing systems. It presents recent developments of such extensions involving reliability modelling theory, reliability evaluation methods, and features numerous case studies based on real-world examples. The presented dynamic reliability theory can enable a more accurate representation of actual complex system behavior, thus more effectively guiding the reliable design of real-world critical systems. Dynamic System Reliability: Modelling and Analysis of Dynamic and Dependent Behaviors begins by describing the evolution from the traditional static reliability theory to the dynamic system reliability theory, and provides a detailed investigation of dynamic and dependent behaviors in subsequent chapters. Although written for those with a background in basic probability theory and stochastic processes, the book includes a chapter reviewing the fundamentals that readers need to know in order to understand contents of other chapters which cover advanced topics in reliability theory and case studies. The first book systematically focusing on dynamic system reliability modelling and analysis theory Provides a comprehensive treatment on imperfect fault coverage (single-level/multi-level or modular), function dependence, common cause failures (deterministic and probabilistic), competing failures (deterministic and probabilistic), and dynamic standby sparing Includes abundant illustrative examples and case studies based on real-world systems Covers recent advances in combinatorial models and algorithms for dynamic system reliability analysis Offers a rich set of references, providing helpful resources for readers to pursue further research and study of the topics Dynamic System Reliability: Modelling and Analysis of Dynamic and Dependent Behaviors is an excellent book for undergraduate and graduate students, and engineers and researchers in reliability and related disciplines.