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The Modeling of Uncertainty in Control Systems

Proceedings of the 1992 Santa Barbara Workshop

  • Conference proceedings
  • © 1994

Overview

Editors:
  1. Roy S. Smith
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  2. Mohammed Dahleh
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Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 192)

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Table of contents (31 papers)

  1. Front Matter

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  2. Identification and robust control

    • Pramod P. Khargonekar
    Pages 1-9

  3. An essay on identification of feedback systems

    • Pertti Mäkilä, Jonathan Partington
    Pages 11-13

  4. Thoughts on identification for control

    • Michael G. Safonov
    Pages 15-17

  5. An essay on robust control

    • Hidenori Kimura
    Pages 19-23

  6. On the character of uncertainty for system identification and robust control design

    • Robert L. Kosut
    Pages 25-28

  7. Extensions of parametric bounding formulation of identification for robust control design

    • J. P. Norton
    Pages 29-34

  8. Connecting identification and robust control

    • Michel Gevers
    Pages 35-37

  9. On nominal models, model uncertainty and iterative methods in identification and control design

    • Paul Van den Hof, Ruud Schrama, Peter Bongers
    Pages 39-50

  10. An informal review of model validation

    • Roy Smith
    Pages 51-59

  11. From data to control

    • Munther A. Dahleh, John C. Doyle
    Pages 61-63

  12. Is robust control reliable?

    • Jeffrey C. Kantor, Billie F. Spencer Jr.
    Pages 65-67

  13. Modeling uncertainty in control systems: A process control perspective

    • Daniel E. Rivera
    Pages 69-75

  14. A note on H ∞ system identification with probabilistic a priori information

    • Clas A. Jacobson, Gilead Tadmor
    Pages 77-92

  15. A worst case identification method using time series data

    • Jie Chen, Carl N. Nett, Michael K. H. Fan
    Pages 93-104

  16. Identification in H ∞ using time-domain measurement data

    • Guoxiang Gu
    Pages 105-116

  17. Identification of feedback systems from time series

    • Pertti Mäkilä, Jonathan Partington
    Pages 117-126

  18. Input-output extrapolation-minimization theorem and its applications to model validation and robust identification

    • Tong Zhou, Hidenori Kimura
    Pages 127-137

  19. Identification of model error bounds in l 1- and H ∞-norm

    • Richard G. Hakvoort, Paul M. J. Van den Hof
    Pages 139-155

  20. Asymptotic worst-case identification with bounded noise

    • Munther A. Dahleh
    Pages 157-170
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Keywords

About this book

This book is a collection of work arising from a NSF/ AFOSR sponsored workshop held at the University of California, Santa Barbara, 18-20th June 1992. Sixty-nine researchers, from nine countries, participated. Twelve keynote essays give an overview of the field and speculate on future directions and nineteen technical papers delineate the state of the art in the field. This book serves both as in introduction to the topic and as a reference on the current technical problems and approaches.

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