Data Driven Modeling Filtering And Control
DOWNLOAD
Download Data Driven Modeling Filtering And Control PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Driven Modeling Filtering And Control 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
Data Driven Modeling Filtering And Control
DOWNLOAD
Author : Carlo Novara
language : en
Publisher:
Release Date : 2019
Data Driven Modeling Filtering And Control written by Carlo Novara and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Filters (Mathematics) categories.
Research in the field of system identification and control has been shifting from traditional model-based to data-driven or evidence-based theories. The latter methods enable better designs based on more direct and accurate data-based information and verifiable data. In the era of big data, IoT, and cyber-physical systems, this subject is of growing importance, as data-driven approaches are key enablers to solve problems that could not be addressed by previous standard approaches. This book presents a number of innovative data-driven methodologies, complemented by significant application examples to show the potential offered by the most recent advances in the field.
Data Driven Modeling Of Cyber Physical Systems Using Side Channel Analysis
DOWNLOAD
Author : Sujit Rokka Chhetri
language : en
Publisher: Springer Nature
Release Date : 2020-02-08
Data Driven Modeling Of Cyber Physical Systems Using Side Channel Analysis written by Sujit Rokka Chhetri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-08 with Technology & Engineering categories.
This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.
Dynamic Modeling Predictive Control And Performance Monitoring
DOWNLOAD
Author : Biao Huang
language : en
Publisher: Springer
Release Date : 2008-03-02
Dynamic Modeling Predictive Control And Performance Monitoring written by Biao Huang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-02 with Technology & Engineering categories.
A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the output predictor from the model; 3. design of the control law or calculation of performance indices according to the predictor. Both design problems need an explicit model form and both require this three-step design procedure. Can this design procedure be simplified? Can an explicit model be avoided? With these questions in mind, the authors eliminate the first and second step of the above design procedure, a “data-driven” approach in the sense that no traditional parametric models are used; hence, the intermediate subspace matrices, which are obtained from the process data and otherwise identified as a first step in the subspace identification methods, are used directly for the designs. Without using an explicit model, the design procedure is simplified and the modelling error caused by parameterization is eliminated.
Data Driven Model Free Controllers
DOWNLOAD
Author : Radu-Emil Precup
language : en
Publisher: CRC Press is
Release Date : 2022
Data Driven Model Free Controllers written by Radu-Emil Precup and has been published by CRC Press is this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Technology & Engineering categories.
This book categorizes the wide area of data-driven model-free controllers, reveals the exact benefits of such controllers, gives the in-depth theory and mathematical proofs behind them, and finally discusses their applications. Each chapter includes a section for presenting the theory and mathematical definitions of one of the above mentioned algorithms. The second section of each chapter is dedicated to the examples and applications of the corresponding control algorithms in practical engineering problems. This book proposes to avoid complex mathematical equations, being generic as it includes several types of data-driven model-free controllers, such as Iterative Feedback Tuning controllers, Model-Free Controllers (intelligent PID controllers), Model-Free Adaptive Controllers, model-free sliding mode controllers, hybrid model‐free and model‐free adaptive‐Virtual Reference Feedback Tuning controllers, hybrid model-free and model-free adaptive fuzzy controllers and cooperative model-free controllers. The book includes the topic of optimal model-free controllers, as well. The optimal tuning of model-free controllers is treated in the chapters that deal with Iterative Feedback Tuning and Virtual Reference Feedback Tuning. Moreover, the extension of some model-free control algorithms to the consensus and formation-tracking problem of multi-agent dynamic systems is provided. This book can be considered as a textbook for undergraduate and postgraduate students, as well as a professional reference for industrial and academic researchers, attracting the readers from both industry and academia.
Data Driven Modeling Filtering And Control
DOWNLOAD
Author : Carlo Novara
language : en
Publisher: Control, Robotics and Sensors
Release Date : 2019-09
Data Driven Modeling Filtering And Control written by Carlo Novara and has been published by Control, Robotics and Sensors this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09 with Technology & Engineering categories.
Using important examples, this book showcases the potential of the latest data-based and data-driven methodologies for filter and control design. It discusses the most important classes of dynamic systems, along with the statistical and set membership analysis and design frameworks.
Data Driven Science And Engineering
DOWNLOAD
Author : Steven L. Brunton
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-05
Data Driven Science And Engineering written by Steven L. Brunton 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 2022-05-05 with Computers categories.
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Data Driven Strategies
DOWNLOAD
Author : Wang Jianhong
language : en
Publisher: CRC Press
Release Date : 2023-03-31
Data Driven Strategies written by Wang Jianhong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-31 with Computers categories.
A key challenge in science and engineering is to provide a quantitative description of the systems under investigation, leveraging the noisy data collected. Such a description may be a complete mathematical model or a mechanism to return controllers corresponding to new, unseen inputs. Recent advances in the theories are described in detail, along with their applications in engineering. The book aims to develop model-free system analysis and control strategies, i.e., data-driven control from theoretical analysis and engineering applications based only on measured data. The study aims to develop system identification, and combination in advanced control theory, i.e., data-driven control strategy as system and controller are generated from measured data directly. The book reviews the development of system identification and its combination in advanced control theory, i.e., data-driven control strategy, as they all depend on measured data. Firstly, data-driven identification is developed for the closed-loop, nonlinear system and model validation, i.e., obtaining model descriptions from measured data. Secondly, the data-driven idea is combined with some control strategies to be considered data-driven control strategies, such as data-driven model predictive control, data-driven iterative tuning control, and data-driven subspace predictive control. Thirdly data-driven identification and data-driven control strategies are applied to interested engineering. In this context, the book provides algorithms to perform state estimation of dynamical systems from noisy data and some convex optimization algorithms through identification and control problems.
Data Driven Modeling And Optimization In Fluid Dynamics From Physics Based To Machine Learning Approaches
DOWNLOAD
Author : Michel Bergmann
language : en
Publisher: Frontiers Media SA
Release Date : 2023-01-05
Data Driven Modeling And Optimization In Fluid Dynamics From Physics Based To Machine Learning Approaches written by Michel Bergmann and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-05 with Science categories.
Control Of Variable Geometry Vehicle Suspensions
DOWNLOAD
Author : Balázs Németh
language : en
Publisher: Springer Nature
Release Date : 2023-07-08
Control Of Variable Geometry Vehicle Suspensions written by Balázs Németh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-08 with Technology & Engineering categories.
This book provides a thorough and fresh treatment of the control of innovative variable-geometry vehicle suspension systems. A deep survey on the topic, which covers the varying types of existing variable-geometry suspension solutions, introduces the study. The book discusses three important aspects of the subject: • robust control design; • nonlinear system analysis; and • integration of learning and control methods. The importance of variable-geometry suspensions and the effectiveness of design methods implemented in the autonomous functionalities of electric vehicles—functionalities like independent steering and torque vectoring—are illustrated. The authors detail the theoretical background of modeling, control design, and analysis for each functionality. The theoretical results achieved through simulation examples and hardware-in-the-loop scenarios are confirmed. The book highlights emerging ideas of applying machine-learning-based methods in the control system with guarantees on safety performance. The authors propose novel control methods, based on the theory of robust linear parameter-varying systems, with examples for various suspension systems. Academic researchers interested in automotive systems and their counterparts involved in industrial research and development will find much to interest them in the eleven chapters of Control of Variable-Geometry Vehicle Suspensions.
Low Rank Approximation
DOWNLOAD
Author : Ivan Markovsky
language : en
Publisher: Springer
Release Date : 2018-08-03
Low Rank Approximation written by Ivan Markovsky and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-03 with Technology & Engineering categories.
This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of applications from systems and control theory to psychometrics being described. Special knowledge of the application fields is not required. The second edition of /Low-Rank Approximation/ is a thoroughly edited and extensively rewritten revision. It contains new chapters and sections that introduce the topics of: • variable projection for structured low-rank approximation;• missing data estimation;• data-driven filtering and control;• stochastic model representation and identification;• identification of polynomial time-invariant systems; and• blind identification with deterministic input model. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB^® /Octave examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis. “Each chapter is completed with a new section of exercises to which complete solutions are provided.” Low-Rank Approximation (second edition) is a broad survey of the Low-Rank Approximation theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well.