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Table of contents

  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 l1- 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
  21. Sequential approximation of uncertainty sets via parallelotopes
    Antonio Vicino, Giovanni Zappa
    Pages 171-180
  22. A robust ellipsoidal-bound approach to direct adaptive control
    Tung-Ching Tsao, Michael G. Safonov
    Pages 181-196
  23. On line model uncertainty quantification: Hard upper bounds and convergence
    Er-Wei Bai, Sundar Raman
    Pages 197-219
  24. A mixed deterministic-probabilistic approach for quantifying uncertainty in Transfer Function Estimation
    Douwe K. de Vries, Paul M. J. Van den Hof
    Pages 221-233
  25. Estimation for robust control
    Brett M. Ninness, Graham C. Goodwin
    Pages 235-259
  26. Non-vanishing model errors
    Håkan Hjalmarsson
    Pages 261-274
  27. Accuracy confidence bands including the bias of model under-fitting
    Wallace E. Larimore
    Pages 275-287
  28. Iterative identification and control design: A worked out example
    Ruud Schrama, Paul Van den Hof
    Pages 289-302
  29. Frequency domain identification for robust control design
    David S. Bayard, Yeung Yam
    Pages 303-335
  30. Time domain approach to the design of integrated control and diagnosis systems
    Hamid Ajbar, Jeffrey C. Kantor
    Pages 337-365
  31. Identification of Ill-conditioned plants — A benchmark problem
    Elling W. Jacobsen, Sigurd Skogestad
    Pages 367-376
  32. Control design and implementation based on experimental wind turbine models
    Peter M. M. Bongers, Gregor E. van Baars
    Pages 377-391
  33. Back Matter
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About these proceedings

Introduction

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.

Keywords

Bias Turbine adaptive control control control system diagnosis feedback information measurement process control robust control system identification uncertainty

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0036239
  • Copyright Information Springer-Verlag 1994
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-19870-3
  • Online ISBN 978-3-540-39327-6
  • Series Print ISSN 0170-8643
  • Series Online ISSN 1610-7411
  • Buy this book on publisher's site