Block Oriented Nonlinear System Identification

Author : Fouad Giri,Er-Wei Bai
Publisher : Unknown
Page : 128 pages
File Size : 55,5 Mb
Release : 2010
Category : Electronic
ISBN : 1849965145

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Block-oriented Nonlinear System Identification by Fouad Giri,Er-Wei Bai Pdf

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 modeling. 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, newcomers, industrial and education practitioners and graduate students alike.

Author : Fouad Giri,Er-Wei Bai
Publisher : Springer Science & Business Media
Page : 425 pages
File Size : 46,6 Mb
Release : 2010-08-18
Category : Technology & Engineering
ISBN : 9781849965125

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Block-oriented Nonlinear System Identification by Fouad Giri,Er-Wei Bai Pdf

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.

Author : Robert Haber,László Keviczky
Publisher : Springer Science & Business Media
Page : 428 pages
File Size : 48,8 Mb
Release : 1999
Category : Computers
ISBN : 0792358570

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Nonlinear system identification. 2. Nonlinear system structure identification by Robert Haber,László Keviczky Pdf

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.

Author : Younghee Han
Publisher : Unknown
Page : 110 pages
File Size : 53,9 Mb
Release : 2012
Category : Electronic
ISBN : 1267424001

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Block-oriented Nonlinear System Identification Using Semidenite Programming by Younghee Han Pdf

Identification of block-oriented nonlinear systems has been an active research area for the last several decades. A block-oriented nonlinear system represents a nonlinear dynamical system as a combination of linear dynamic systems and static nonlinear blocks. In block-oriented nonlinear systems, each block (linear dynamic systems and static nonlinearity) can be connected in many different ways (series, parallel, feedback) and this flexibility provides the block-oriented modeling approach with an ability to capture a large class of nonlinear systems. However, intermediate signals in such block-oriented systems are not measurable and the inaccessibility of such measurements is the main difficulty in block-oriented nonlinear system identification. Recently a system identification method using rank minimization has been introduced for linear system identification. Finding the simplest model within a feasible model set restricted by convex constraints can often be formulated as a rank minimization problem. In this research, the rank minimization approach is extended to block-oriented nonlinear system identification. The system parameter estimation problem is formulated as a rank minimization problem or the combination of prediction error and rank minimization problems by constraining a finite dimensional time dependency of a linear dynamic system and by using the monotonicity of static nonlinearity. This allows us to reconstruct non-measurable intermediate signals and once the intermediate signals have been reconstructed, the identification of each block can be solved with the standard Prediction Error method or Least Squares method. The research work presented in this dissertation proposes a new approach for block-oriented system identification by tackling the inaccessibility of measurement of intermediate signals in block-oriented nonlinear systems via rank minimization. Since the rank minimization problem is non-convex, the rank minimization problem is relaxed to a semidefinite programming problem by minimizing the nuclear norm instead of the rank. The research contributes to advances in block-oriented nonlinear system identification.

Author : Andrzej Janczak
Publisher : Springer Science & Business Media
Page : 220 pages
File Size : 43,9 Mb
Release : 2004-11-18
Category : Technology & Engineering
ISBN : 3540231854

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Identification of Nonlinear Systems Using Neural Networks and Polynomial Models by Andrzej Janczak Pdf

This monograph systematically presents the existing identification methods of nonlinear systems using the block-oriented approach It surveys various known approaches to the identification of Wiener and Hammerstein systems which are applicable to both neural network and polynomial models. The book gives a comparative study of their gradient approximation accuracy, computational complexity, and convergence rates and furthermore presents some new and original methods concerning the model parameter adjusting with gradient-based techniques. "Identification of Nonlinear Systems Using Neural Networks and Polynomal Models" is useful for researchers, engineers and graduate students in nonlinear systems and neural network theory.

Author : Grzegorz Mzyk
Publisher : Springer
Page : 238 pages
File Size : 47,7 Mb
Release : 2013-11-20
Category : Technology & Engineering
ISBN : 9783319035963

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Combined Parametric-Nonparametric Identification of Block-Oriented Systems by Grzegorz Mzyk Pdf

This book considers a problem of block-oriented nonlinear dynamic system identification in the presence of random disturbances. This class of systems includes various interconnections of linear dynamic blocks and static nonlinear elements, e.g., Hammerstein system, Wiener system, Wiener-Hammerstein ("sandwich") system and additive NARMAX systems with feedback. Interconnecting signals are not accessible for measurement. The combined parametric-nonparametric algorithms, proposed in the book, can be selected dependently on the prior knowledge of the system and signals. Most of them are based on the decomposition of the complex system identification task into simpler local sub-problems by using non-parametric (kernel or orthogonal) regression estimation. In the parametric stage, the generalized least squares or the instrumental variables technique is commonly applied to cope with correlated excitations. Limit properties of the algorithms have been shown analytically and illustrated in simple experiments.

Author : Y. Zhu
Publisher : Elsevier
Page : 372 pages
File Size : 40,7 Mb
Release : 2001-10-08
Category : Technology & Engineering
ISBN : 9780080537115

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Multivariable System Identification For Process Control by Y. Zhu Pdf

Systems and control theory has experienced significant development in the past few decades. New techniques have emerged which hold enormous potential for industrial applications, and which have therefore also attracted much interest from academic researchers. However, the impact of these developments on the process industries has been limited. The purpose of Multivariable System Identification for Process Control is to bridge the gap between theory and application, and to provide industrial solutions, based on sound scientific theory, to process identification problems. The book is organized in a reader-friendly way, starting with the simplest methods, and then gradually introducing more complex techniques. Thus, the reader is offered clear physical insight without recourse to large amounts of mathematics. Each method is covered in a single chapter or section, and experimental design is explained before any identification algorithms are discussed. The many simulation examples and industrial case studies demonstrate the power and efficiency of process identification, helping to make the theory more applicable. MatlabTM M-files, designed to help the reader to learn identification in a computing environment, are included.

Author : Paul Van Den Hof,Bo Wahlberg,Siep Weiland
Publisher : Elsevier
Page : 2088 pages
File Size : 45,6 Mb
Release : 2004-06-29
Category : Technology & Engineering
ISBN : 9780080913155

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System Identification 2003 by Paul Van Den Hof,Bo Wahlberg,Siep Weiland Pdf

The scope of the symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control, ranging from theoretical, methodological and scientific developments to a large variety of (engineering) application areas. It is the intention of the organizers to promote SYSID 2003 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas. Relevant topics for the symposium program include: Identification of linear and multivariable systems, identification of nonlinear systems, including neural networks, identification of hybrid and distributed systems, Identification for control, experimental modelling in process control, vibration and modal analysis, model validation, monitoring and fault detection, signal processing and communication, parameter estimation and inverse modelling, statistical analysis and uncertainty bounding, adaptive control and data-based controller tuning, learning, data mining and Bayesian approaches, sequential Monte Carlo methods, including particle filtering, applications in process control systems, motion control systems, robotics, aerospace systems, bioengineering and medical systems, physical measurement systems, automotive systems, econometrics, transportation and communication systems *Provides the latest research on System Identification *Contains contributions written by experts in the field *Part of the IFAC Proceedings Series which provides a comprehensive overview of the major topics in control engineering.

Author : Wlodzimierz Greblicki,Miroslaw Pawlak
Publisher : Cambridge University Press
Page : 0 pages
File Size : 49,5 Mb
Release : 2012-10-04
Category : Technology & Engineering
ISBN : 1107410622

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Nonparametric System Identification by Wlodzimierz Greblicki,Miroslaw Pawlak Pdf

Presenting a thorough overview of the theoretical foundations of non-parametric system identification for nonlinear block-oriented systems, this books shows that non-parametric regression can be successfully applied to system identification, and it highlights the achievements in doing so. With emphasis on Hammerstein, Wiener systems, and their multidimensional extensions, the authors show how to identify nonlinear subsystems and their characteristics when limited information exists. Algorithms using trigonometric, Legendre, Laguerre, and Hermite series are investigated, and the kernel algorithm, its semirecursive versions, and fully recursive modifications are covered. The theories of modern non-parametric regression, approximation, and orthogonal expansions, along with new approaches to system identification (including semiparametric identification), are provided. Detailed information about all tools used is provided in the appendices. This book is for researchers and practitioners in systems theory, signal processing, and communications and will appeal to researchers in fields like mechanics, economics, and biology, where experimental data are used to obtain models of systems.

Author : Wlodzimierz Greblicki,Greblicki Weodzimierz Pawlak M,Mirosław Pawlak
Publisher : Unknown
Page : 402 pages
File Size : 41,9 Mb
Release : 2014-05-14
Category : Science
ISBN : 0511409826

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Nonparametric System Identification by Wlodzimierz Greblicki,Greblicki Weodzimierz Pawlak M,Mirosław Pawlak Pdf

Author : Stan Matwin,Jan Mielniczuk
Publisher : Springer
Page : 399 pages
File Size : 54,7 Mb
Release : 2015-07-07
Category : Technology & Engineering
ISBN : 9783319187815

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Challenges in Computational Statistics and Data Mining by Stan Matwin,Jan Mielniczuk Pdf

This volume contains nineteen research papers belonging to the areas of computational statistics, data mining, and their applications. Those papers, all written specifically for this volume, are their authors’ contributions to honour and celebrate Professor Jacek Koronacki on the occcasion of his 70th birthday. The book’s related and often interconnected topics, represent Jacek Koronacki’s research interests and their evolution. They also clearly indicate how close the areas of computational statistics and data mining are.

Author : J. Mikles,M. Huba
Publisher : Elsevier
Page : 436 pages
File Size : 55,6 Mb
Release : 2014-05-23
Category : Technology & Engineering
ISBN : 9781483296975

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New Trends in Design of Control Systems 1994 by J. Mikles,M. Huba Pdf

Computer control systems are developing rapidly, therefore an insight of the latest trends in the design of control systems will increase the success of future developments. This publication brings together the latest key papers on research and development trends in this field, allowing both academics and industrial practioners to find new insights and gain from each other's experience.

Author : Przemysław Sliwinski
Publisher : Springer Science & Business Media
Page : 146 pages
File Size : 46,9 Mb
Release : 2012-10-12
Category : Mathematics
ISBN : 9783642293955

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Nonlinear System Identification by Haar Wavelets by Przemysław Sliwinski Pdf

​In order to precisely model real-life systems or man-made devices, both nonlinear and dynamic properties need to be taken into account. The generic, black-box model based on Volterra and Wiener series is capable of representing fairly complicated nonlinear and dynamic interactions, however, the resulting identification algorithms are impractical, mainly due to their computational complexity. One of the alternatives offering fast identification algorithms is the block-oriented approach, in which systems of relatively simple structures are considered. The book provides nonparametric identification algorithms designed for such systems together with the description of their asymptotic and computational properties. ​ ​

Author : Rohit Thanki,Purva Joshi
Publisher : Springer Nature
Page : 105 pages
File Size : 47,8 Mb
Release : 2023-06-27
Category : Technology & Engineering
ISBN : 9783031332388

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Advanced Technologies for Industrial Applications by Rohit Thanki,Purva Joshi Pdf

This book provides information on advanced communication technology used in Industry 4.0 and 5.0. The book covers a variety of technologies such as signal processing, system designing, computer vision, and artificial intelligence and explains their benefits, usage, and market values in Industry 4.0 and 5.0. The authors present technological tools for industrial applications and give examples of their usage of system design, modeling, artificial intelligence, internet of things and robotics. This book covers the impact of these technologies in various industrial applications and provides future technological tools that will be helpful in future planning and development. The book is pertinent to researchers, academics, professionals, planners, and student’s interest in Industry 5.0.

Author : Matthew S. Allen,Randall L. Mayes,Daniel Jean Rixen
Publisher : Springer
Page : 370 pages
File Size : 54,6 Mb
Release : 2017-04-23
Category : Science
ISBN : 9783319549309

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Dynamics of Coupled Structures, Volume 4 by Matthew S. Allen,Randall L. Mayes,Daniel Jean Rixen Pdf

Dynamics of Coupled Structures, Volume 4: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the fourth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of the Dynamics of Coupled Structures, including papers on: Experimental Nonlinear Dynamics Joints, Friction & Damping Nonlinear Substructuring Transfer Path Analysis and Source Characterization Analytical Substructuring & Numerical Reduction Techniques Real Time Substructuring Assembling & Decoupling Substructures & Boundary Conditions