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Friday, July 31, 2020 | History

1 edition of System Identification and Robust Control found in the catalog.

System Identification and Robust Control

a Case Study Approach

by Steen TГёffner-Clausen

  • 70 Want to read
  • 21 Currently reading

Published by Springer London in London .
Written in English

    Subjects:
  • Engineering

  • About the Edition

    The main theme of this book is robust control design from a practical point of view. A thorough introduction to frequency response norm-based robust control design methods is given. This includes, in particular, a comprehensive treatment of the structural singular value . An important problem in robust control design is how to determine model uncertainty. In this book it is shown how system identification can be used to obtain error bounds for use in subsequent controller design. Both classical prediction error methods and the more recent Stochastic Embedding Approach are treated and a step-by-step procedure for system identification based robust control design is provided. The design techniques presented in the book are illustrated through numerous case studies including, for example, the control design for an ASTOVL (Advanced Short Take-Off and Vertical Landing) aircraft.

    Edition Notes

    Statementby Steen Tøffner-Clausen
    SeriesAdvances in Industrial Control, Advances in industrial control
    Classifications
    LC ClassificationsTJ212-225
    The Physical Object
    Format[electronic resource] :
    Pagination1 online resource (XXVI, 311 pages 91 illustrations).
    Number of Pages311
    ID Numbers
    Open LibraryOL27090579M
    ISBN 101447115139, 1447115155
    ISBN 109781447115137, 9781447115151
    OCLC/WorldCa858877492

    EE Intelligent Control Systems. COURSE OUTLINE. Updated: Saturday, Ma Systems and Controls Thrust Area. EE Homepage. PDF file of the book. F.L. Lewis, L. Xie, and D. Popa, Optimal & Robust Estimation: With an Introduction to Stochastic Control Theory, CRC Press, Boca Raton, Second Edition. PDF file of the book. This development has drawn upon progress in identification, control system design, robust control, adaptive control and computer aided control engineering. It has also indicated that there are a number of good research problems in the area that remains to be solved.

      I used a portfolio of books, since my classes in control engineering covered a variety of topics. The three main books that I used were: [1] R. C. Dorf and R. H. Bishop. Modern Control Systems. Pearson Education, Upper Saddle River, NJ, elev.   Books System Identification and Robust Control: A Case Study Approach (Advances in Industrial.

    Reviewer: Arvid G. Larson The aim of this book is to provide the knowledge necessary for the comprehension and implementation of digital techniques for system identification and control, by eliminating on the one hand all theoretical developments that are unnecessary for the user, and on the other hand, taking into account the availability of the identification and control . System identification for robust and inferential control: with applications to ILC and precision motion systems Citation for published version (APA): Oomen, T. A. E. (). System identification for robust and inferential control: with applications to ILC and precision motion by:


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System Identification and Robust Control by Steen TГёffner-Clausen Download PDF EPUB FB2

System Identification and Robust Control: A Case Study Approach (Advances in Industrial Control) Softcover reprint of the original 1st ed. Edition byCited by: 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. 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.

So far we have mainly considered robust control and system identification independently. This reflects the traditional segregation of the two fields within the automatic control community.

In this part of the book we will suggest various schemes which combines the results from robust control presented in Part I with the results from system identification presented in Part : Steen Tøffner-Clausen. In this article, dynamic modeling, system identification, and robust control system implementation of roll and pitch dynamics of an unmanned helicopter is performed.

A TRexE radio-controlled helicopter is equipped with a novel low-cost flight control system designed and constructed based on Raspberry Pi Linux-based : Mohammad Hossein Khalesi, Hassan Salarieh, Mahmoud Saadat Foumani.

Robust Identification and Control Article neural networks for dynamic system identification and control have been created, performance of the training algorithms has been analyzed, and the.

In order to take full advantage of this potential, Digital System Identification and Robust Control book Systems demonstrates in detail how to design and implement high-performance model-based controllers combining system identification and control design techniques extensively tested in industrial milieux.

The effective use of these techniques is illustrated in the context of various systems including: d.c. Brand: Springer-Verlag London. TY - BOOK. T1 - System Identification and Robust Control. T2 - A Case Study Approach. AU - Tøffner-Clausen, S. PY - Y1 - M3 - Book.

SN - T3 - Advances in Industrial Control. BT - System Identification and Robust Control. PB - IEEE Computer Society Press. CY - London. ER. It is shown that unfalsification of the standard robust control design uncertainty model is a natural replacement for system identification when the intended use of the model is robust control.

In this paper a framework for connecting system identification and robust control design via a factorization approach is being introduced. Within the scope of this framework, models are represented in an estimated set of models that is used subsequently to design a robust performing by: 7.

Abstract: This paper studies the system identification and robust control of a multi-input multi-output (MIMO) active magnetic bearing (AMB) system. The AMB system under study is open-loop unstable, and the presence of right-half plane zeros and the rotor flexible modes bring additional degrees of difficulty to the control design of such a by:   His research interests encompass theory and applications in system identification, adaptive control, robust digital control and nonlinear systems.

He has authored and co-authored over papers on these subjects. Increasing performance demands in control applications necessitate accurate modeling of complex systems for control. The aim of this chapter is to develop a new system identification algorithm that delivers models that are suitable for subsequent robust control design and can be reliably applied to complex systems.

To achieve this, an identification algorithm is developed Cited by: 3. State-of-the-art modeling and motion control design procedures do not deliver the required model complexity and fidelity to control the flexible dynamical behavior.

The aim of this paper is to develop a combined system identification and robust control design procedure for high performance motion control and apply it to a wafer by: This book consisting of eight chapters covers the main topics on industrial systems, system identification, nonlinear control design, optimal control, adaptive control, robust control and applications to variety of engineering systems.

This book provides a thorough "guided tour" of the various control design techniques applied to a variety of Cited by: System Identification and Robust Control: a Case Study Approach. [Steen Tøffner-Clausen] -- The main theme of this book is robust control design from a practical point of view.

A thorough introduction to frequency response norm-based robust control design methods is given. “Practical” Identification • Given: •Want 1) a model for the plant 2) a model for the noise 3) an estimate of the accuracy • choice of the model structureFile Size: 1MB.

Estimation and Control of Large Scale Networked Systems is the first book that systematically summarizes results on large-scale networked addition, the book also summarizes the most recent results on structure identification of a networked system, attack identification.

The book is written in a self-contained fashion to be used as a textbook on adaptive systems at the senior undergraduate, or flrst and second gradu- ate level. It is assumed that the reader is familiar with the materials taught in undergraduate courses on linear systems, difierential equations, and auto- matic control.

Spaces and Norms in Robust Control Theory Robust Control Design using Singular Values Robust Control Design using Structured Singular Values Mixed [mu] Control of a Compact Disc Servo Drive [mu] Control of an Ill-Conditioned Aircraft Introduction to Estimation Theory Classical System Identification Orthonormal Filters in System Identification.

This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors. provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system.In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation.

This book complements the existing literature on the identification of CT systems by.Identification for control. In control systems applications, the objective of engineers is to obtain a good performance of the closed-loop system, which is the one comprising the physical system, the feedback loop and the controller.

This performance is typically achieved by designing the control law relying on a model of the system.