The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples designed for Ljung's market-leading software, System Identification Toolbox for MATLAB. Ljung combines careful mathematics, a practical understanding of real-world applications, and extensive exercises. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods. Parameter estimation methods in a general prediction error setting. Frequency domain data and frequency domain interpretations. Asymptotic analysis of parameter estimates. Linear regressions, iterative search methods, and other ways to compute estimates. Recursive (adaptive) estimation techniques. Ljung also presents detailed coverage of the key issues that can make or break system identification projects, such as defining objectives, designing experiments, controlling the bias distribution of transfer-function estimates, and carefully validating the resulting models. The first edition of System Identification has been the field's most widely cited reference for over a decade. This new edition will be the new text of choice for anyone concerned with system identification theory and practice.
Author: Rik Pintelon
Publisher: John Wiley & Sons
Release Date: 2012-03-19
System identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and the designing of any electrical systems, they are vital in the fields of electrical, mechanical, civil, and chemical engineering. Focusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach. It high??lights many of the important steps in the identification process, points out the possible pitfalls to the reader, and illustrates the powerful tools that are available. Readers of this Second Editon will benefit from: MATLAB software support for identifying multivariable systems that is freely available at the website http://booksupport.wiley.com State-of-the-art system identification methods for both time and frequency domain data New chapters on non-parametric and parametric transfer function modeling using (non-)period excitations Numerous examples and figures that facilitate the learning process A simple writing style that allows the reader to learn more about the theo??retical aspects of the proofs and algorithms Unlike other books in this field, System Identification, Second Edition is ideal for practicing engineers, scientists, researchers, and both master's and PhD students in electrical, mechanical, civil, and chemical engineering.
Master Techniques and Successfully Build Models Using a Single Resource Vital to all data-driven or measurement-based process operations, system identification is an interface that is based on observational science, and centers on developing mathematical models from observed data. Principles of System Identification: Theory and Practice is an introductory-level book that presents the basic foundations and underlying methods relevant to system identification. The overall scope of the book focuses on system identification with an emphasis on practice, and concentrates most specifically on discrete-time linear system identification. Useful for Both Theory and Practice The book presents the foundational pillars of identification, namely, the theory of discrete-time LTI systems, the basics of signal processing, the theory of random processes, and estimation theory. It explains the core theoretical concepts of building (linear) dynamic models from experimental data, as well as the experimental and practical aspects of identification. The author offers glimpses of modern developments in this area, and provides numerical and simulation-based examples, case studies, end-of-chapter problems, and other ample references to code for illustration and training. Comprising 26 chapters, and ideal for coursework and self-study, this extensive text: Provides the essential concepts of identification Lays down the foundations of mathematical descriptions of systems, random processes, and estimation in the context of identification Discusses the theory pertaining to non-parametric and parametric models for deterministic-plus-stochastic LTI systems in detail Demonstrates the concepts and methods of identification on different case-studies Presents a gradual development of state-space identification and grey-box modeling Offers an overview of advanced topics of identification namely the linear time-varying (LTV), non-linear, and closed-loop identification Discusses a multivariable approach to identification using the iterative principal component analysis Embeds MATLAB® codes for illustrated examples in the text at the respective points Principles of System Identification: Theory and Practice presents a formal base in LTI deterministic and stochastic systems modeling and estimation theory; it is a one-stop reference for introductory to moderately advanced courses on system identification, as well as introductory courses on stochastic signal processing or time-series analysis.
Effective system identification includes the underlying methodologies, computational procedures, and their implementation. To this end, this volume presents readers with the mathematical background required to participate in the growing field of system identification as applied to engineering systems. Author Jer-Nan Juang provides a common basis for understanding the techniques developed under various disciplines. In addition, he attempts to bring the discipline of system identification up to date. Specifically Applied System Identification: provides an overview of the disciplines of modal testing used in structural engineering and system identification; presents time- and frequency-domain models used in the disciplines of structures and controls; identifies basic concepts and properties of the frequency response function; features a unified mathematical framework based on the theory of system realization to correlate some of the existing time-domain methods commonly used in modal testing; introduces readers to a new way of interpreting the input/output relationship via an observer for identification of a system model and its corresponding observer to characterize system uncertainties; proposes a simple, yet effective way of curve-fitting the frequency response data and of constructing a system model via matrix-fraction description methods; considers the identification problem of a system operating in closed-loop with an existing feedback controller; develops a unified mathematical framework to derive recursive algorithms for the fast transversal filter and the least-squares lattice filter. Whether used as a textbook or as an addition to your personal reference library, Applied System Identification offers an ideal opportunity to build a bridge between the disciplines of system identification as applied to controls and to modal testing.
Author: Lennart Ljung
Publisher: Prentice Hall
Release Date: 1994
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.
Author: Johan Schoukens
Publisher: John Wiley & Sons
Release Date: 2012-04-02
Genre: Technology & Engineering
This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring complex theoretical knowledge. The contents encompass state-of-the-art system identification methods, with both time and frequency domain system identification methods covered, including the pros and cons of each. Each chapter features MATLAB exercises, discussions of the exercises, accompanying MATLAB downloads, and larger projects that serve as potential assignments in this learn-by-doing resource.
Author: Charles M. Hansen
Publisher: CRC Press
Release Date: 2007-06-15
Hansen solubility parameters (HSPs) are used to predict molecular affinities, solubility, and solubility-related phenomena. Revised and updated throughout, Hansen Solubility Parameters: A User's Handbook, Second Edition features the three Hansen solubility parameters for over 1200 chemicals and correlations for over 400 materials including polymers, inorganic salts, and biological materials. To update his groundbreaking handbook with the latest advances and perspectives, Charles M. Hansen has invited five renowned experts to share their work, theories, and practical applications involving HSPs. New discussions include a new statistical thermodynamics approach for confirming existing HSPs and how they fit into other thermodynamic theories for polymer solutions. Entirely new chapters examine the prediction of environmental stress cracking as well as absorption and diffusion in polymers. Highlighting recent findings on interactions with DNA, the treatment of biological materials also includes skin tissue, proteins, natural fibers, and cholesterol. The book also covers the latest applications of HSPs, such as ozone-safe “designer” solvents, protective clothing, drug delivery systems, and petroleum applications. Presenting a comprehensive survey of the theoretical and practical aspects of HSPs, Hansen Solubility Parameters, Second Edition concludes with a detailed discussion on the necessary research, future directions, and potential applications for which HSPs can provide a useful means of prediction in areas such as biological materials, controlled release applications, nanotechnology, and self-assembly.
This thoroughly updated third edition of Critical Theory Today offers an accessible introduction to contemporary critical theory, providing in-depth coverage of the most common approaches to literary analysis today, including: feminism; psychoanalysis; Marxism; reader-response theory; New Criticism; structuralism and semiotics; deconstruction; new historicism and cultural criticism; lesbian, gay, and queer theory; African American criticism and postcolonial criticism. This new edition features: a major expansion of the chapter on postcolonial criticism that includes topics such as Nordicism, globalization and the ‘end’ of postcolonial theory, global tourism and global conservation an extended explanation of each theory, using examples from everyday life, popular culture, and literary texts a list of specific questions critics ask about literary texts an interpretation of F. Scott Fitzgerald's The Great Gatsby through the lens of each theory a list of questions for further practice to guide readers in applying each theory to different literary works updated and expanded bibliographies Both engaging and rigorous, this is a "how-to" book for undergraduate and graduate students new to critical theory and for college professors who want to broaden their repertoire of critical approaches to literature.
This reference book can be read at different levels, making it a powerful source of information. It presents most of the aspects of control that can help anyone to have a synthetic view of control theory and possible applications, especially concerning process engineering.
Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make optimal decisions under uncertainty; model and evaluate computer systems and networks; and prepare for advanced probability-based courses. Written in a lively style with simple language, this classroom-tested book can now be used in both one- and two-semester courses. New to the Second Edition Axiomatic introduction of probability Expanded coverage of statistical inference, including standard errors of estimates and their estimation, inference about variances, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap More exercises at the end of each chapter Additional MATLAB® codes, particularly new commands of the Statistics Toolbox In-Depth yet Accessible Treatment of Computer Science-Related Topics Starting with the fundamentals of probability, the text takes students through topics heavily featured in modern computer science, computer engineering, software engineering, and associated fields, such as computer simulations, Monte Carlo methods, stochastic processes, Markov chains, queuing theory, statistical inference, and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). Encourages Practical Implementation of Skills Using simple MATLAB commands (easily translatable to other computer languages), the book provides short programs for implementing the methods of probability and statistics as well as for visualizing randomness, the behavior of random variables and stochastic processes, convergence results, and Monte Carlo simulations. Preliminary knowledge of MATLAB is not required. Along with numerous computer science applications and worked examples, the text presents interesting facts and paradoxical statements. Each chapter concludes with a short summary and many exercises.
Author: Victor O. Sadras
Release Date: 2014-09-17
Genre: Technology & Engineering
From climate change to farming systems to genetic modification of organisms, Crop Physiology, Second Edition provides a practical tool for understanding the relationships and challenges of successful cropping. With a focus on genetic improvement and agronomy, this book addresses the challenges of environmentally sound production of bulk and quality food, fodder, fiber, and energy which are of ongoing international concern. The second edition of Crop Physiology continues to provide a unique analysis of these topics while reflecting important changes and advances in the relevant science and implementation systems. Contemporary agriculture confronts the challenge of increasing demand in terms of quantitative and qualitative production targets. These targets have to be achieved against the background of soil and water scarcity, worldwide and regional shifts in the patterns of land use driven by both climate change and the need to develop crop-based sources of energy, and the environmental and social aspects of agricultural sustainability. Provides a view of crop physiology as an active source of methods, theories, ideas, and tools for application in genetic improvement and agronomy Written by leading scientists from around the world Combines environment-specific cropping systems and general principles of crop science to appeal to advanced students, and scientists in agriculture-related disciplines, from molecular sciences to natural resources management
Author: Ian C. Kemp
Release Date: 2011-04-01
Genre: Technology & Engineering
Pinch analysis and related techniques are the key to design of inherently energy-efficient plants. This book shows engineers how to understand and optimize energy use in their processes, whether large or small. Energy savings go straight to the bottom line as increased profit, as well as reducing emissions. This is the key guide to process integration for both experienced and newly qualified engineers, as well as academics and students. It begins with an introduction to the main concepts of pinch analysis, the calculation of energy targets for a given process, the pinch temperature and the golden rules of pinch-based design to meet energy targets. The book shows how to extract the stream data necessary for a pinch analysis and describes the targeting process in depth. Other essential details include the design of heat exchanger networks, hot and cold utility systems, CHP (combined heat and power), refrigeration and optimization of system operating conditions. Many tips and techniques for practical application are covered, supported by several detailed case studies and other examples covering a wide range of industries, including buildings and other non-process situations. The only dedicated pinch analysis and process integration guide, fully revised and expanded supported by free downloadable energy targeting software The perfect guide and reference for chemical process, food and biochemical engineers, plant engineers and professionals concerned with energy optimisation, including building designers Covers the practical analysis of both new and existing systems, with ful details of industrial applications and case studies
Author: Yanwei Wang
Publisher: Morgan & Claypool Publishers
Release Date: 2005
Genre: Technology & Engineering
Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar, and underwater acoustics. Most existing spectral estimation algorithms are devised for uniformly sampled complete-data sequences. However, the spectral estimation for data sequences with missing samples is also important in a wide range of applications.This lecture considers the spectral estimation problem in the case where some of the data samples are missing. The challenge is how to extend the existing spectral estimation techniques to deal with these missing-data samples. Recently, nonparametric adaptive filtering based techniques have been developed successfully for various missing-data spectral estimation problems. Collectively, these algorithms provide a comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches. They provide the main topic of this lecture..The authors present the recently developed nonparametric adaptive filtering based algorithms for the missing-data case, namely gapped-data APES (GAPES) and the more general missing-data APES (MAPES).
Author: John J. HAMPTON
Publisher: AMACOM Div American Mgmt Assn
Release Date: 2009-08-05
Genre: Business & Economics
Using examples from companies such as Home Depot, Airbus, Boeing, and Nokia, Fundamentals of Enterprise Risk Management takes a fresh look at one of the hottest topics in business today. Showing readers in charge of monitoring operational exposures in corporations, nonprofit organizations, and government agencies how they can best determine and balance opportunities against the possibilities of loss, this book provides clear strategies to help readers: • recognize both internal and external exposures • understand important concepts such as risk mapping and risk identification • recognize the weaknesses of current ERM systems • align risk opportunities with their organization’s business model • stay in line with Sarbanes-Oxley compliance The book introduces innovative new concepts such as hierarchical risk structures, alignment of risks with the business model, creation of a central risk function, and the role of an ERM knowledge warehouse. Featuring enlightening case studies and practical exercises, this essential book shows readers how they can implement ERM the right way at their organizations.