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Author: N.H. McClamroch
Publisher: Springer Science & Business Media
ISBN: 1461260876
Category : Technology & Engineering
Languages : en
Pages : 257
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Book Description
The purpose of this book is to expose undergraduate students to the use of applied mathematics and physical argument as a basis for developing an understanding of the response characteristics, from a systems viewpoint, of a broad class of dynamic physical processes. This book was developed for use in the course ECE 355, Dynamic Systems and Modeling, in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor. The course ECE 355 has been elected primarily by junior and senior level students in computer engineering or in electrical engineering. Occasionally a student from outside these two programs elected the course. Thus the book is written with this class of students in mind. It is assumed that the reader has previous background in mathematics through calculus, differential equations, and Laplace transforms, in elementary physics, and in elemen tary mechanics and circuits. Although these prerequisites indicate the orientation of the material, the book should be accessible and of interest to students with a much wider spectrum of experience in applied mathemati cal topics. The subject matter of the book can be considered to form an introduc tion to the theory of mathematical systems presented from a modern, as opposed to a classical, point of view. A number of physical processes are examined where the underlying systems concepts can be clearly seen and grasped. The organization of the book around case study examples has evolved as a consequence of student suggestions.
Author: N.H. McClamroch
Publisher: Springer Science & Business Media
ISBN: 1461260876
Category : Technology & Engineering
Languages : en
Pages : 257
Get Book
Book Description
The purpose of this book is to expose undergraduate students to the use of applied mathematics and physical argument as a basis for developing an understanding of the response characteristics, from a systems viewpoint, of a broad class of dynamic physical processes. This book was developed for use in the course ECE 355, Dynamic Systems and Modeling, in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor. The course ECE 355 has been elected primarily by junior and senior level students in computer engineering or in electrical engineering. Occasionally a student from outside these two programs elected the course. Thus the book is written with this class of students in mind. It is assumed that the reader has previous background in mathematics through calculus, differential equations, and Laplace transforms, in elementary physics, and in elemen tary mechanics and circuits. Although these prerequisites indicate the orientation of the material, the book should be accessible and of interest to students with a much wider spectrum of experience in applied mathemati cal topics. The subject matter of the book can be considered to form an introduc tion to the theory of mathematical systems presented from a modern, as opposed to a classical, point of view. A number of physical processes are examined where the underlying systems concepts can be clearly seen and grasped. The organization of the book around case study examples has evolved as a consequence of student suggestions.
Author: Charles M. Close
Publisher: John Wiley & Sons
ISBN: 0471394424
Category : Technology & Engineering
Languages : en
Pages : 592
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Book Description
The third edition of Modeling and Anaysis of Dynamic Systems continues to present students with the methodology applicable to the modeling and analysis of a variety of dynamic systems, regardless of their physical origin. It includes detailed modeling of mechanical, electrical, electro-mechanical, thermal, and fluid systems. Models are developed in the form of state-variable equations, input-output differential equations, transfer functions, and block diagrams. The Laplace transform is used for analytical solutions. Computer solutions are based on MATLAB and Simulink. Examples include both linear and nonlinear systems. An introduction is given to the modeling and design tools for feedback control systems. The text offers considerable flexibility in the selection of material for a specific course. Students majoring in many different engineering disciplines have used the text. Such courses are frequently followed by control-system design courses in the various disciplines.
Author: Steven L. Brunton
Publisher: Cambridge University Press
ISBN: 1009098489
Category : Computers
Languages : en
Pages : 615
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Book Description
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author: Patricia Mellodge
Publisher: Woodhead Publishing
ISBN: 0081002246
Category : Mathematics
Languages : en
Pages : 292
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Book Description
A Practical Approach to Dynamical Systems for Engineers takes the abstract mathematical concepts behind dynamical systems and applies them to real-world systems, such as a car traveling down the road, the ripples caused by throwing a pebble into a pond, and a clock pendulum swinging back and forth. Many relevant topics are covered, including modeling systems using differential equations, transfer functions, state-space representation, Hamiltonian systems, stability and equilibrium, and nonlinear system characteristics with examples including chaos, bifurcation, and limit cycles. In addition, MATLAB is used extensively to show how the analysis methods are applied to the examples. It is assumed readers will have an understanding of calculus, differential equations, linear algebra, and an interest in mechanical and electrical dynamical systems. Presents applications in engineering to show the adoption of dynamical system analytical methods Provides examples on the dynamics of automobiles, aircraft, and human balance, among others, with an emphasis on physical engineering systems MATLAB and Simulink are used throughout to apply the analysis methods and illustrate the ideas Offers in-depth discussions of every abstract concept, described in an intuitive manner, and illustrated using practical examples, bridging the gap between theory and practice Ideal resource for practicing engineers who need to understand background theory and how to apply it
Author: Nathaniel McClamroch
Publisher: Springer
ISBN: 9781461260882
Category : Technology & Engineering
Languages : en
Pages : 248
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Book Description
The purpose of this book is to expose undergraduate students to the use of applied mathematics and physical argument as a basis for developing an understanding of the response characteristics, from a systems viewpoint, of a broad class of dynamic physical processes. This book was developed for use in the course ECE 355, Dynamic Systems and Modeling, in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor. The course ECE 355 has been elected primarily by junior and senior level students in computer engineering or in electrical engineering. Occasionally a student from outside these two programs elected the course. Thus the book is written with this class of students in mind. It is assumed that the reader has previous background in mathematics through calculus, differential equations, and Laplace transforms, in elementary physics, and in elemen tary mechanics and circuits. Although these prerequisites indicate the orientation of the material, the book should be accessible and of interest to students with a much wider spectrum of experience in applied mathemati cal topics. The subject matter of the book can be considered to form an introduc tion to the theory of mathematical systems presented from a modern, as opposed to a classical, point of view. A number of physical processes are examined where the underlying systems concepts can be clearly seen and grasped. The organization of the book around case study examples has evolved as a consequence of student suggestions.
Author: Rama K. Yedavalli
Publisher: Springer Science & Business Media
ISBN: 1461491320
Category : Technology & Engineering
Languages : en
Pages : 204
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Book Description
This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the “real world” system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework. Illustrates various systems level methodologies with examples and applications drawn from aerospace, electrical and mechanical engineering. Provides connections between lyapunov-based matrix approach and the transfer function based polynomial approaches. Robust Control of Uncertain Dynamic Systems: A Linear State Space Approach is an ideal book for first year graduate students taking a course in robust control in aerospace, mechanical, or electrical engineering.
Author: Rudy Slingerland
Publisher: Princeton University Press
ISBN: 1400839114
Category : Science
Languages : en
Pages : 246
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Book Description
A concise guide to representing complex Earth systems using simple dynamic models Mathematical Modeling of Earth's Dynamical Systems gives earth scientists the essential skills for translating chemical and physical systems into mathematical and computational models that provide enhanced insight into Earth's processes. Using a step-by-step method, the book identifies the important geological variables of physical-chemical geoscience problems and describes the mechanisms that control these variables. This book is directed toward upper-level undergraduate students, graduate students, researchers, and professionals who want to learn how to abstract complex systems into sets of dynamic equations. It shows students how to recognize domains of interest and key factors, and how to explain assumptions in formal terms. The book reveals what data best tests ideas of how nature works, and cautions against inadequate transport laws, unconstrained coefficients, and unfalsifiable models. Various examples of processes and systems, and ample illustrations, are provided. Students using this text should be familiar with the principles of physics, chemistry, and geology, and have taken a year of differential and integral calculus. Mathematical Modeling of Earth's Dynamical Systems helps earth scientists develop a philosophical framework and strong foundations for conceptualizing complex geologic systems. Step-by-step lessons for representing complex Earth systems as dynamical models Explains geologic processes in terms of fundamental laws of physics and chemistry Numerical solutions to differential equations through the finite difference technique A philosophical approach to quantitative problem-solving Various examples of processes and systems, including the evolution of sandy coastlines, the global carbon cycle, and much more Professors: A supplementary Instructor's Manual is available for this book. It is restricted to teachers using the text in courses. For information on how to obtain a copy, refer to: http://press.princeton.edu/class_use/solutions.html
Author: Juš Kocijan
Publisher: Springer
ISBN: 3319210211
Category : Technology & Engineering
Languages : en
Pages : 267
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Book Description
This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.
Author: Avi Pfeffer
Publisher: Simon and Schuster
ISBN: 1638352372
Category : Computers
Languages : en
Pages : 650
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Book Description
Summary Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In it, you'll learn how to use the PP paradigm to model application domains and then express those probabilistic models in code. Although PP can seem abstract, in this book you'll immediately work on practical examples, like using the Figaro language to build a spam filter and applying Bayesian and Markov networks, to diagnose computer system data problems and recover digital images. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The data you accumulate about your customers, products, and website users can help you not only to interpret your past, it can also help you predict your future! Probabilistic programming uses code to draw probabilistic inferences from data. By applying specialized algorithms, your programs assign degrees of probability to conclusions. This means you can forecast future events like sales trends, computer system failures, experimental outcomes, and many other critical concerns. About the Book Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In this book, you’ll immediately work on practical examples like building a spam filter, diagnosing computer system data problems, and recovering digital images. You’ll discover probabilistic inference, where algorithms help make extended predictions about issues like social media usage. Along the way, you’ll learn to use functional-style programming for text analysis, object-oriented models to predict social phenomena like the spread of tweets, and open universe models to gauge real-life social media usage. The book also has chapters on how probabilistic models can help in decision making and modeling of dynamic systems. What's Inside Introduction to probabilistic modeling Writing probabilistic programs in Figaro Building Bayesian networks Predicting product lifecycles Decision-making algorithms About the Reader This book assumes no prior exposure to probabilistic programming. Knowledge of Scala is helpful. About the Author Avi Pfeffer is the principal developer of the Figaro language for probabilistic programming. Table of Contents PART 1 INTRODUCING PROBABILISTIC PROGRAMMING AND FIGARO Probabilistic programming in a nutshell A quick Figaro tutorial Creating a probabilistic programming application PART 2 WRITING PROBABILISTIC PROGRAMS Probabilistic models and probabilistic programs Modeling dependencies with Bayesian and Markov networks Using Scala and Figaro collections to build up models Object-oriented probabilistic modeling Modeling dynamic systems PART 3 INFERENCE The three rules of probabilistic inference Factored inference algorithms Sampling algorithms Solving other inference tasks Dynamic reasoning and parameter learning
Author: Asish Ghosh
Publisher: Springer
ISBN: 3319107356
Category : Science
Languages : en
Pages : 239
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Book Description
This book is a study of the interactions between different types of systems, their environment, and their subsystems. The author explains how basic systems principles are applied in engineered (mechanical, electromechanical, etc.) systems and then guides the reader to understand how the same principles can be applied to social, political, economic systems, as well as in everyday life. Readers from a variety of disciplines will benefit from the understanding of system behaviors and will be able to apply those principles in various contexts. The book includes many examples covering various types of systems. The treatment of the subject is non-mathematical, and the book considers some of the latest concepts in the systems discipline, such as agent-based systems, optimization, and discrete events and procedures.
