Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Nonlinear System Identification 2 Nonlinear System Structure Identification
Download Nonlinear System Identification 2 Nonlinear System Structure Identification full books in PDF, epub, and Kindle. Read online Nonlinear System Identification 2 Nonlinear System Structure Identification ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Nonlinear system identification. 2. Nonlinear system structure identification by : Robert Haber
Download or read book Nonlinear system identification. 2. Nonlinear system structure identification written by Robert Haber and published by Springer Science & Business Media. This book was released on 1999 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second part of a two-volume handbook presenting a comprehensive overview of nonlinear dynamic system identification. The books include many aspects of nonlinear processes such as modelling, parameter estimation, structure search, nonlinearity and model validity tests.
Book Synopsis Nonlinear system identification. 1. Nonlinear system parameter identification by : Robert Haber
Download or read book Nonlinear system identification. 1. Nonlinear system parameter identification written by Robert Haber and published by Springer Science & Business Media. This book was released on 1999 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonlinear System Identification by : Stephen A. Billings
Download or read book Nonlinear System Identification written by Stephen A. Billings and published by John Wiley & Sons. This book was released on 2013-07-29 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) model The orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model term Statistical and qualitative model validation methods that can be applied to any model class Generalised frequency response functions which provide significant insight into nonlinear behaviours A completely new class of filters that can move, split, spread, and focus energy The response spectrum map and the study of sub harmonic and severely nonlinear systems Algorithms that can track rapid time variation in both linear and nonlinear systems The important class of spatio-temporal systems that evolve over both space and time Many case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all included to demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems NARMAX algorithms provide a fundamentally different approach to nonlinear system identification and signal processing for nonlinear systems. NARMAX methods provide models that are transparent, which can easily be analysed, and which can be used to solve real problems. This book is intended for graduates, postgraduates and researchers in the sciences and engineering, and also for users from other fields who have collected data and who wish to identify models to help to understand the dynamics of their systems.
Book Synopsis Nonlinear System Identification by : Oliver Nelles
Download or read book Nonlinear System Identification written by Oliver Nelles and published by Springer Nature. This book was released on 2020-09-09 with total page 1235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides engineers and scientists in academia and industry with a thorough understanding of the underlying principles of nonlinear system identification. It equips them to apply the models and methods discussed to real problems with confidence, while also making them aware of potential difficulties that may arise in practice. Moreover, the book is self-contained, requiring only a basic grasp of matrix algebra, signals and systems, and statistics. Accordingly, it can also serve as an introduction to linear system identification, and provides a practical overview of the major optimization methods used in engineering. The focus is on gaining an intuitive understanding of the subject and the practical application of the techniques discussed. The book is not written in a theorem/proof style; instead, the mathematics is kept to a minimum, and the ideas covered are illustrated with numerous figures, examples, and real-world applications. In the past, nonlinear system identification was a field characterized by a variety of ad-hoc approaches, each applicable only to a very limited class of systems. With the advent of neural networks, fuzzy models, Gaussian process models, and modern structure optimization techniques, a much broader class of systems can now be handled. Although one major aspect of nonlinear systems is that virtually every one is unique, tools have since been developed that allow each approach to be applied to a wide variety of systems.
Book Synopsis Block-oriented Nonlinear System Identification by : Fouad Giri
Download or read book Block-oriented Nonlinear System Identification written by Fouad Giri and published by Springer Science & Business Media. This book was released on 2010-08-18 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Block-oriented Nonlinear System Identification deals with an area of research that has been very active since the turn of the millennium. The book makes a pedagogical and cohesive presentation of the methods developed in that time. These include: iterative and over-parameterization techniques; stochastic and frequency approaches; support-vector-machine, subspace, and separable-least-squares methods; blind identification method; bounded-error method; and decoupling inputs approach. The identification methods are presented by authors who have either invented them or contributed significantly to their development. All the important issues e.g., input design, persistent excitation, and consistency analysis, are discussed. The practical relevance of block-oriented models is illustrated through biomedical/physiological system modelling. The book will be of major interest to all those who are concerned with nonlinear system identification whatever their activity areas. This is particularly the case for educators in electrical, mechanical, chemical and biomedical engineering and for practising engineers in process, aeronautic, aerospace, robotics and vehicles control. Block-oriented Nonlinear System Identification serves as a reference for active researchers, new comers, industrial and education practitioners and graduate students alike.
Book Synopsis Nonlinear System Identification by : Oliver Nelles
Download or read book Nonlinear System Identification written by Oliver Nelles and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 785 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
Book Synopsis New Methods for System Identification of Nonlinear Structures by : Michael Kwarta
Download or read book New Methods for System Identification of Nonlinear Structures written by Michael Kwarta and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: System identification plays a significant role in engineering design process, since it helps in correlating numerical or mathematical models with the actual real-life structures. Once the virtual representation of a mechanical system is found, it can be further used in: (i) predicting the structure's motion or (ii) redesigning or optimizing the structure. Many system identification methods are available which have found success in identifying certain linear and/or nonlinear systems. However, there are many nonlinear cases where the algorithms are still not successful in identifying an accurate model from measurements. Much work is still needed in this field to develop a toolbox of methods that can give adequate results when applied to any system, just as linear system identification can handle almost any linear system. Nonlinear Normal Modes (NNMs) are a common way to express the dynamics of a nonlinear structure over a range of amplitudes since they are independent of the forcing applied to the system. NNMs can be estimated experimentally and further used to correlate, validate, and update the mathematical or numerical representations of the system. Naturally, there are different kinds of methods that can be used to extract the NNM curve from measurements. Each of these nonlinear system identification techniques tries to handle the problem in its own original way. Hence, they can be classified into different categories based on the domain they operate in, or models they use. The primary contribution of this work is the development and demonstration of two new techniques for nonlinear system identification. The first one utilizes near-resonant steady-state harmonically excited vibration measurements to estimate the Nonlinear Normal Mode backbones. The algorithm can be classified as a modal method since it is based on the previously proposed Single Nonlinear Resonant Mode (SNRM) formula and uses it in a new and more effective way. Namely, it can estimate one point on the nonlinear mode from only one steady-state measurement collected near the resonance. Compared to some of the existing methods of similar type, the proposed technique can reduce the time required to obtain measurements and avoids difficulties due to e.g. the premature jump phenomenon. The other technique operates in the frequency domain and tries to fit a differential equation to the transient measurements to estimate the terms in the nonlinear equation of motion (EOM). Nonlinear terms are added to the linear EOM in the form of polynomials, and the proposed algorithm seeks to estimate the polynomial coefficients. This method requires the user to postulate a form for the nonlinearity. However, this work also presents an extension that revealed an interesting black-box identification capability. The algorithms are first evaluated numerically using benchmark case studies, such as the Duffing equation or reduced models of clamped-clamped flat and curved beams. Then the methods are employed experimentally to estimate the NNM backbones of beams that were manufactured from polylactide using a 3D printer and experience significant eigen-frequency shifts when the motion amplitude increases. The results are validated against measurements collected using the traditional phase resonance testing or swept-sine approaches.
Book Synopsis Identification of Nonlinear Physiological Systems by : David T. Westwick
Download or read book Identification of Nonlinear Physiological Systems written by David T. Westwick and published by John Wiley & Sons. This book was released on 2003-08-28 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Significant advances have been made in the field since the previous classic texts were written. This text brings the available knowledge up to date. * Enables the reader to use a wide variety of nonlinear system identification techniques. * Offers a thorough treatment of the underlying theory. * Provides a MATLAB toolbox containing implementation of the latest identification methods together with an extensive set of problems using realistic data sets.
Book Synopsis Block-oriented Nonlinear System Identification by : Fouad Giri
Download or read book Block-oriented Nonlinear System Identification written by Fouad Giri and published by Springer. This book was released on 2010-09-22 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Block-oriented Nonlinear System Identification deals with an area of research that has been very active since the turn of the millennium. The book makes a pedagogical and cohesive presentation of the methods developed in that time. These include: iterative and over-parameterization techniques; stochastic and frequency approaches; support-vector-machine, subspace, and separable-least-squares methods; blind identification method; bounded-error method; and decoupling inputs approach. The identification methods are presented by authors who have either invented them or contributed significantly to their development. All the important issues e.g., input design, persistent excitation, and consistency analysis, are discussed. The practical relevance of block-oriented models is illustrated through biomedical/physiological system modelling. The book will be of major interest to all those who are concerned with nonlinear system identification whatever their activity areas. This is particularly the case for educators in electrical, mechanical, chemical and biomedical engineering and for practising engineers in process, aeronautic, aerospace, robotics and vehicles control. Block-oriented Nonlinear System Identification serves as a reference for active researchers, new comers, industrial and education practitioners and graduate students alike.
Book Synopsis Nonlinearity in Structural Dynamics by : K Worden
Download or read book Nonlinearity in Structural Dynamics written by K Worden and published by CRC Press. This book was released on 2019-04-23 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many types of engineering structures exhibit nonlinear behavior under real operating conditions. Sometimes the unpredicted nonlinear behavior of a system results in catastrophic failure. In civil engineering, grandstands at sporting events and concerts may be prone to nonlinear oscillations due to looseness of joints, friction, and crowd movements.
Book Synopsis Nonlinear System Identification — Input-Output Modeling Approach by : Robert Haber
Download or read book Nonlinear System Identification — Input-Output Modeling Approach written by Robert Haber and published by Springer. This book was released on 2012-12-22 with total page 802 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of case studies on the modeling and identifications of real processes illustrate the methods. Almost all processes are nonlinear if they are considered not merely in a small vicinity of the working point. To exploit industrial equipment as much as possible, mathematical models are needed which describe the global nonlinear behavior of the process. If the process is unknown, or if the describing equations are too complex, the structure and the parameters can be determined experimentally, which is the task of identification. The book is divided into seven chapters dealing with the following topics: 1. Nonlinear dynamic process models 2. Test signals for identification 3. Parameter estimation methods 4. Nonlinearity test methods 5. Structure identification 6. Model validity tests 7. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems.
Book Synopsis System Identification by : Lennart Ljung
Download or read book System Identification written by Lennart Ljung and published by Pearson Education. This book was released on 1998-12-29 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Principles of System Identification by : Arun K. Tangirala
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
Book Synopsis System Identification for Structured Nonlinear Systems by : Mareike Silke Claassen
Download or read book System Identification for Structured Nonlinear Systems written by Mareike Silke Claassen and published by . This book was released on 2001 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Normal Modes and Localization in Nonlinear Systems by : Alexander F. Vakakis
Download or read book Normal Modes and Localization in Nonlinear Systems written by Alexander F. Vakakis and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nonlinear normal modes of a parametrically excited cantilever beam are constructed by directly applying the method of multiple scales to the governing integral-partial differential equation and associated boundary conditions. The effect of the inertia and curvature nonlin earities and the parametric excitation on the spatial distribution of the deflection is examined. The results are compared with those obtained by using a single-mode discretization. In the absence of linear viscous and quadratic damping, it is shown that there are nonlinear normal modes, as defined by Rosenberg, even in the presence of a principal parametric excitation. Furthermore, the nonlinear mode shape obtained with the direct approach is compared with that obtained with the discretization approach for some values of the excitation frequency. In the single-mode discretization, the spatial distribution of the deflection is assumed a priori to be given by the linear mode shape ¢n, which is parametrically excited, as Equation (41). Thus, the mode shape is not influenced by the nonlinear curvature and nonlinear damping. On the other hand, in the direct approach, the mode shape is not assumed a priori; the nonlinear effects modify the linear mode shape ¢n. Therefore, in the case of large-amplitude oscillations, the single-mode discretization may yield inaccurate mode shapes. References 1. Vakakis, A. F., Manevitch, L. I., Mikhlin, Y. v., Pilipchuk, V. N., and Zevin A. A., Nonnal Modes and Localization in Nonlinear Systems, Wiley, New York, 1996.
Book Synopsis Adaptive Nonlinear System Identification by : Tokunbo Ogunfunmi
Download or read book Adaptive Nonlinear System Identification written by Tokunbo Ogunfunmi and published by Springer. This book was released on 2008-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes. Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.
Book Synopsis System Identification and Adaptive Control by : Yiannis Boutalis
Download or read book System Identification and Adaptive Control written by Yiannis Boutalis and published by Springer Science & Business. This book was released on 2014-04-23 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
