Download or read book Optimal Experiment Design for Dynamic System Identification written by M B Zarrop and published by Springer. This book was released on 2014-01-15 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimal Experiment Design for Dynamic System Identification written by M.B. Zarrop and published by Springer. This book was released on 1979-12 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimal Experiment Design and System Identification written by Martin Cody Priess and published by . This book was released on 2015 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamic System Identification Experiment Design and Data Analysis written by Goodwin and published by Academic Press. This book was released on 1977-11-10 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic System Identification: Experiment Design and Data Analysis
Download or read book Optimal Measurement Methods for Distributed Parameter System Identification written by Dariusz Ucinski and published by CRC Press. This book was released on 2004-08-27 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software systems. With the expense of scanning and moving sensors, optimal placement presents a critical problem.
Download or read book Essays on Control written by H.L. Trentelman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the text of the plenary lectures and the mini-courses of the European Control Conference (ECC'93) held in Groningen, the Netherlands, June 2S-July 1, 1993. However, the book is not your usu al conference proceedings. Instead, the authors took this occasion to take a broad overview of the field of control and discuss its development both from a theoretical as well as from an engineering perpective. The first essay is by the key-note speaker ofthe conference, A.G.J. Mac Farlane. It consists of a non-technical discussion of information processing and knowledge acquisition as the key features of control engineering tech nology. The next six articles are accounts of the plenary addresses. The contribution by R.W. Brockett concerns a mathematical framework for modelling motion control, a central question in robotics and vision. In the paper by M. Morari the engineering and the economic relevance of chemical process control are considered, in particular statistical quality control and the control of systems with constraints. The article by A.C.P.M. Backx is written from an industrial perspec tive. The author is director of an engineering consulting firm involved in the design of industrial control equipment. Specifically, the possibility of obtaining high performance and reliable controllers by modelling, identifi cation, and optimizing industrial processes is discussed.
Download or read book Optimal experiment design for dynamic system identification written by Robert Luxmore Payne and published by . This book was released on 1974 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Trends and Progress in System Identification written by Pieter Eykhoff and published by Elsevier. This book was released on 2014-05-20 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trends and Progress in System Identification is a three-part book that focuses on model considerations, identification methods, and experimental conditions involved in system identification. Organized into 10 chapters, this book begins with a discussion of model method in system identification, citing four examples differing on the nature of the models involved, the nature of the fields, and their goals. Subsequent chapters describe the most important aspects of model theory; the ""classical"" methods and time series estimation; application of least squares and related techniques for the estimation of dynamic system parameters; the maximum likelihood and error prediction methods; and the modern development of statistical methods. Non-parametric approaches, identification of nonlinear systems by piecewise approximation, and the minimax identification are then explained. Other chapters explore the Bayesian approach to system identification; choice of input signals; and choice and effect of different feedback configurations in system identification. This book will be useful for control engineers, system scientists, biologists, and members of other disciplines dealing withdynamical relations.
Download or read book System Identification written by Karel J. Keesman and published by Springer Science & Business Media. This book was released on 2011-05-16 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering: • data-based identification – non-parametric methods for use when prior system knowledge is very limited; • time-invariant identification for systems with constant parameters; • time-varying systems identification, primarily with recursive estimation techniques; and • model validation methods. A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text. The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input–output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors’ Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable for self-tuition by practitioners looking to brush up on modern techniques. Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.
Download or read book Interactive System Identification Prospects and Pitfalls written by Torsten Bohlin and published by Springer Science & Business Media. This book was released on 2013-03-13 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: The craft of designing mathematical models of dynamic objects offers a large number of methods to solve subproblems in the design, typically parameter estimation, order determination, validation, model reduc tion, analysis of identifiability, sensi tivi ty and accuracy. There is also a substantial amount of process identification software available. A typi cal 'identification package' consists of program modules that implement selections of solution methods, coordinated by supervising programs, communication, and presentation handling file administration, operator of results. It is to be run 'interactively', typically on a designer's 'work station' . However, it is generally not obvious how to do that. Using interactive identification packages necessarily leaves to the user to decide on quite a number of specifications, including which model structure to use, which subproblems to be solved in each particular case, and in what or der. The designer is faced with the task of setting up cases on the work station, based on apriori knowledge about the actual physical object, the experiment conditions, and the purpose of the identification. In doing so, he/she will have to cope with two basic difficulties: 1) The com puter will be unable to solve most of the tentative identification cases, so the latter will first have to be form11lated in a way the computer can handle, and, worse, 2) even in cases where the computer can actually produce a model, the latter will not necessarily be valid for the intended purpose.
Download or read book System Identification Environmental Modelling and Control System Design written by Liuping Wang and published by Springer Science & Business Media. This book was released on 2011-10-20 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is dedicated to Prof. Peter Young on his 70th birthday. Professor Young has been a pioneer in systems and control, and over the past 45 years he has influenced many developments in this field. This volume comprises a collection of contributions by leading experts in system identification, time-series analysis, environmetric modelling and control system design – modern research in topics that reflect important areas of interest in Professor Young’s research career. Recent theoretical developments in and relevant applications of these areas are explored treating the various subjects broadly and in depth. The authoritative and up-to-date research presented here will be of interest to academic researcher in control and disciplines related to environmental research, particularly those to with water systems. The tutorial style in which many of the contributions are composed also makes the book suitable as a source of study material for graduate students in those areas.
Download or read book An Introduction to Identification written by J. P. Norton and published by Courier Corporation. This book was released on 2009-01-01 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for advanced undergraduates and graduate students, this text covers the theoretical basis for mathematical modeling as well as a variety of identification algorithms and their applications. 1986 edition.
Download or read book System Identification written by Rik Pintelon and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electrical Engineering System Identification A Frequency Domain Approach How does one model a linear dynamic system from noisy data? This book presents a general approach to this problem, with both practical examples and theoretical discussions that give the reader a sound understanding of the subject and of the pitfalls that might occur on the road from raw data to validated model. The emphasis is on robust methods that can be used with a minimum of user interaction. Readers in many fields of engineering will gain knowledge about: * Choice of experimental setup and experiment design * Automatic characterization of disturbing noise * Generation of a good plant model * Detection, qualification, and quantification of nonlinear distortions * Identification of continuous- and discrete-time models * Improved model validation tools and from the theoretical side about: * System identification * Interrelations between time- and frequency-domain approaches * Stochastic properties of the estimators * Stochastic analysis System Identification: A Frequency Domain Approach is written for practicing engineers and scientists who do not want to delve into mathematical details of proofs. Also, it is written for researchers who wish to learn more about the theoretical aspects of the proofs. Several of the introductory chapters are suitable for undergraduates. Each chapter begins with an abstract and ends with exercises, and examples are given throughout.
Download or read book Identification for Automotive Systems written by Daniel Alberer and published by Springer Science & Business Media. This book was released on 2011-12-09 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.
Download or read book Bounding Approaches to System Identification written by M. Milanese and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.
Download or read book Optimum Experimental Designs With SAS written by Anthony Atkinson and published by OUP Oxford. This book was released on 2007-05-24 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis. This book presents the theory and methods of optimum experimental design, making them available through the use of SAS programs. Little previous statistical knowledge is assumed. The first part of the book stresses the importance of models in the analysis of data and introduces least squares fitting and simple optimum experimental designs. The second part presents a more detailed discussion of the general theory and of a wide variety of experiments. The book stresses the use of SAS to provide hands-on solutions for the construction of designs in both standard and non-standard situations. The mathematical theory of the designs is developed in parallel with their construction in SAS, so providing motivation for the development of the subject. Many chapters cover self-contained topics drawn from science, engineering and pharmaceutical investigations, such as response surface designs, blocking of experiments, designs for mixture experiments and for nonlinear and generalized linear models. Understanding is aided by the provision of "SAS tasks" after most chapters as well as by more traditional exercises and a fully supported website. The authors are leading experts in key fields and this book is ideal for statisticians and scientists in academia, research and the process and pharmaceutical industries.
Download or read book Principles of System Identification written by Arun K. Tangirala and published by CRC Press. This book was released on 2018-10-08 with total page 908 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.The MATLAB scripts and SIMULINK models used as examples and case studies in the book are also available on the author's website: http://arunkt.wix.com/homepage#!textbook/c397
