Control Oriented System Identification

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Control Oriented System Identification
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Author : Jie Chen
language : en
Publisher: Wiley-Interscience
Release Date : 2000-06-19
Control Oriented System Identification written by Jie Chen and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-06-19 with Science categories.
This volume covers system identification. Identification, in the language of control theory, is the process of obtaining a model of the object or process being controlled.
Block Oriented Nonlinear System Identification
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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.
Control Oriented System Identification
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Author :
language : en
Publisher:
Release Date : 1993
Control Oriented System Identification written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
The research goals for this grant were to obtain algorithms for control oriented system identification is to construct dynamical models of systems based primarily on measured data that are compatible with robust control design techniques. The research carried out under this grant has continued the research on control oriented identification originated by the PI and his collaborators, has extended control oriented identification methods to new classes of dynamical systems and has initiated a study unifying identification and control laws design. The research that has extended existing problem formulation concerns the construction of algorithms for linear shift invariant systems using a combination of apriori and experimental information. Algorithms for the identification of continuous time systems and efficient linear algorithms have been constructed. The research that has extended the existing problem formulation concerns the development of algorithms for the construction of parameterized linear families form a combination of apriori and measured information. Algorithms for this type of nonlinear system identification have been given that produce models suitable for gain scheduled controllers. Finally research into the integration control oriented identification and robust control for slowly time varying systems was initiated under this grant.
System Identification
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Author : Karel J. Keesman
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-05-16
System Identification written by Karel J. Keesman 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 2011-05-16 with Technology & Engineering categories.
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.
System Identification And Robust Control
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Author : Steen Toffner-Clausen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
System Identification And Robust Control written by Steen Toffner-Clausen 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 2012-12-06 with Technology & Engineering categories.
The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies, ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The present text Steen T0ffner-Clausen deals with both system identification and robust control. It provides a very comprehensive tutorial introduction to some of the most difficult topics in robust control theory before considering applications problems. Traditional Hoo robust control design concepts for multivariable systems are first considered and the problems of robust stability and performance are discussed. The following chapter introduces the idea of the structured singular value and applies this to both analysis and synthesis problems. The author manages to provide a very straightforward introduction to this subject and also introduces some new ideas.
Identification And Control Using Volterra Models
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Author : F.J.III Doyle
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Identification And Control Using Volterra Models written by F.J.III Doyle 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 2012-12-06 with Technology & Engineering categories.
Much has been written about the general difficulty of developing the models required for model-based control of processes whose dynamics exhibit signif icant nonlinearity (for further discussion and references, see Chapter 1). In fact, the development ofthese models stands as a significant practical imped iment to widespread industrial application oftechniques like nonlinear model predictive control (NMPC), whoselinear counterpart has profoundly changed industrial practice. One ofthe reasons for this difficulty lies in the enormous variety of "nonlinear models," different classes of which can be less similar to each other than they are to the class of linear models. Consequently, it is a practical necessity to restrict consideration to one or a few specific nonlinear model classes if we are to succeed in developing, understanding, and using nonlinear models as a basis for practical control schemes. Because they repre sent a highly structured extension ofthe class oflinear finite impulse response (FIR) models on which industrially popular linear MPC implementations are based, this book is devoted to the class of discrete-time Volterra models and a fewother, closelyrelated, nonlinear model classes. The objective ofthis book is to provide a useful reference for researchers in the field of process control and closely related areas, collecting a reasonably wide variety of results that may be found in different parts of the large literature that exists on the gen eral topics of process control, nonlinear systems theory, statistical time-series models, biomedical engineering, and digital signal processing, among others.
Nonlinear System Identification
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Author : Oliver Nelles
language : en
Publisher: Springer Nature
Release Date : 2020-09-09
Nonlinear System Identification written by Oliver Nelles and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-09 with Science categories.
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.
Signal Analysis And Prediction
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Author : Ales Prochazka
language : en
Publisher: Springer Science & Business Media
Release Date : 1998-12-23
Signal Analysis And Prediction written by Ales Prochazka 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 1998-12-23 with Technology & Engineering categories.
Methods of signal analysis represent a broad research topic with applications in many disciplines, including engineering, technology, biomedicine, seismography, eco nometrics, and many others based upon the processing of observed variables. Even though these applications are widely different, the mathematical background be hind them is similar and includes the use of the discrete Fourier transform and z-transform for signal analysis, and both linear and non-linear methods for signal identification, modelling, prediction, segmentation, and classification. These meth ods are in many cases closely related to optimization problems, statistical methods, and artificial neural networks. This book incorporates a collection of research papers based upon selected contri butions presented at the First European Conference on Signal Analysis and Predic tion (ECSAP-97) in Prague, Czech Republic, held June 24-27, 1997 at the Strahov Monastery. Even though the Conference was intended as a European Conference, at first initiated by the European Association for Signal Processing (EURASIP), it was very gratifying that it also drew significant support from other important scientific societies, including the lEE, Signal Processing Society of IEEE, and the Acoustical Society of America. The organizing committee was pleased that the re sponse from the academic community to participate at this Conference was very large; 128 summaries written by 242 authors from 36 countries were received. In addition, the Conference qualified under the Continuing Professional Development Scheme to provide PD units for participants and contributors.
Robust Control Oriented Linear Fractional Transform Modelling
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Author : Tamal Roy
language : en
Publisher: Springer Nature
Release Date : 2023-01-03
Robust Control Oriented Linear Fractional Transform Modelling written by Tamal Roy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-03 with Technology & Engineering categories.
This book covers a new paradigm of system modeling – the robust control-oriented linear fractional transformation (LFT) modeling. A dynamic system expressed in LFT modeling framework paves the way for the application of modern robust controller design technique like μ-synthesis method for controller design. This book covers the generalized robust control-oriented LFT modeling representation of the MIMO system depending upon the uncertainty structure, system dynamics, and the dimensions of the input–output. The modeling framework results into a compact and manageable representation of uncertainty modeling in the form of feedback-like structure that is suitable for design and implementation of the robust control technique like μ-synthesis-based H∞ control theory. This book also describes the application of the proposed methodology in a variety of advanced mechatronic systems like the Twin Rotor MIMO system, wheeled mobile robot, and an industrial robot arm.
Identification For Automotive Systems
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Author : Daniel Alberer
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-12-09
Identification For Automotive Systems written by Daniel Alberer 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 2011-12-09 with Technology & Engineering categories.
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.