Block Oriented Nonlinear System Identification Using Semidenite Programming
DOWNLOAD
Download Block Oriented Nonlinear System Identification Using Semidenite Programming PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Block Oriented Nonlinear System Identification Using Semidenite Programming book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Block Oriented Nonlinear System Identification Using Semidenite Programming
DOWNLOAD
Author : Younghee Han
language : en
Publisher:
Release Date : 2012
Block Oriented Nonlinear System Identification Using Semidenite Programming written by Younghee Han and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
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.
Adaptive Learning Methods For Nonlinear System Modeling
DOWNLOAD
Author : Danilo Comminiello
language : en
Publisher: Butterworth-Heinemann
Release Date : 2018-06-11
Adaptive Learning Methods For Nonlinear System Modeling written by Danilo Comminiello and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-11 with Technology & Engineering categories.
Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. - Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. - Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. - Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.
Data Driven Methods For Dynamic Systems
DOWNLOAD
Author : Jason Bramburger
language : en
Publisher: SIAM
Release Date : 2024-11-05
Data Driven Methods For Dynamic Systems written by Jason Bramburger and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-05 with Science categories.
As experimental data sets have grown and computational power has increased, new tools have been developed that have the power to model new systems and fundamentally alter how current systems are analyzed. This book brings together modern computational tools to provide an accurate understanding of dynamic data. The techniques build on pencil-and-paper mathematical techniques that go back decades and sometimes even centuries. The result is an introduction to state-of-the-art methods that complement, rather than replace, traditional analysis of time-dependent systems. Data-Driven Methods for Dynamic Systems provides readers with methods not found in other texts as well as novel ones developed just for this book; an example-driven presentation that provides background material and descriptions of methods without getting bogged down in technicalities; and examples that demonstrate the applicability of a method and introduce the features and drawbacks of their application. The online supplementary material includes a code repository that can be used to reproduce every example and that can be repurposed to fit a variety of applications not found in the book. This book is intended as an introduction to the field of data-driven methods for graduate students. It will also be of interest to researchers who want to familiarize themselves with the discipline. It can be used in courses on dynamical systems, differential equations, and data science.
D Compositions Matricielles Et Tensorielles En Traitement Du Signal
DOWNLOAD
Author : Gérard Favier
language : fr
Publisher: ISTE Group
Release Date : 2022-04-01
D Compositions Matricielles Et Tensorielles En Traitement Du Signal written by Gérard Favier and has been published by ISTE Group this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-01 with Science categories.
À l’ère du Big Data, le traitement de l’information numérique occupe une place centrale dans de nombreux domaines applicatifs. Dans ce contexte, les tenseurs sont aujourd’hui de plus en plus utilisés pour la représentation, la compression, l’analyse, la classification et la fusion de données massives, multidimensionnelles et multimodales. Didactique, cet ouvrage débute par une présentation de différentes applications basées sur des approches tensorielles et un rappel des principales décompositions matricielles, puis il étudie de façon détaillée les produits de Hadamard, de Kronecker et de Khatri-Rao en faisant appel à une convention indicielle utile pour le calcul tensoriel. Les principales opérations tensorielles sont ensuite décrites et illustrées à l’aide de nombreux exemples. L’ouvrage introduit également les notions de valeur propre et de valeur singulière d’un tenseur et considère le problème fondamental de la meilleure approximation d’un tenseur. Il présente enfin les décompositions tensorielles de base, avec des illustrations issues d’applications en traitement du signal.
Block Oriented Nonlinear System Identification
DOWNLOAD
Author : Fouad Giri
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-08-18
Block Oriented Nonlinear System Identification written by Fouad Giri and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-18 with Technology & Engineering categories.
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.
Documentation Abstracts
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1997
Documentation Abstracts written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Documentation categories.
International Aerospace Abstracts
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1997
International Aerospace Abstracts written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Aeronautics categories.
Filtering And System Identification
DOWNLOAD
Author : Michel Verhaegen
language : en
Publisher: Cambridge University Press
Release Date : 2012-07-19
Filtering And System Identification written by Michel Verhaegen and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-19 with Technology & Engineering categories.
Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127.
Feedback Systems
DOWNLOAD
Author : Karl Johan Åström
language : en
Publisher: Princeton University Press
Release Date : 2021-02-02
Feedback Systems written by Karl Johan Åström and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-02 with Technology & Engineering categories.
The essential introduction to the principles and applications of feedback systems—now fully revised and expanded This textbook covers the mathematics needed to model, analyze, and design feedback systems. Now more user-friendly than ever, this revised and expanded edition of Feedback Systems is a one-volume resource for students and researchers in mathematics and engineering. It has applications across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl Åström and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Åström and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. Features a new chapter on design principles and tools, illustrating the types of problems that can be solved using feedback Includes a new chapter on fundamental limits and new material on the Routh-Hurwitz criterion and root locus plots Provides exercises at the end of every chapter Comes with an electronic solutions manual An ideal textbook for undergraduate and graduate students Indispensable for researchers seeking a self-contained resource on control theory
Convex Optimization
DOWNLOAD
Author : Stephen P. Boyd
language : en
Publisher: Cambridge University Press
Release Date : 2004-03-08
Convex Optimization written by Stephen P. Boyd and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-08 with Business & Economics categories.
Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.