Robustness in Identification and Control

  • M. Milanese
  • R. Tempo
  • A. Vicino

Part of the Applied Information Technology book series

Table of contents

  1. Front Matter
    Pages i-viii
  2. Robust Identification and Complexity

  3. Robust Stability and Control

    1. Front Matter
      Pages 77-77
    2. John J. Anagnost, Charles A. Desoer, Robert J. Minnichelli
      Pages 79-96
    3. M. Mansour, F. Kraus, B. D. O. Anderson
      Pages 109-124
    4. Hervé Chapellat, S. P. Bhattacharyya
      Pages 207-229
    5. F. J. Kraus, M. Mansour, B. D. O. Anderson
      Pages 263-280
    6. Peter Dorato, Yunzhi Li, Hong Bae Park
      Pages 321-327
    7. M. Corless, D. Da
      Pages 329-337
  4. Back Matter
    Pages 339-341

About this book


This volume collects most of the papers presented at the International Workshop on Robustness in Identification and Control, held in Torino (Italy) in 1988. The main focal point of the workshop was Unknown But Bounded uncertainty and associated robustness issues in identification and control. Recent years have seen a growing interest in studying models which include un­ known but bounded uncertainty. The motivation for dealing with such models is derived from robustness considerations. In many applications, some performance specification must be met for all admissible variations of the uncertain parameters. A second motivation for models with this type of uncertainty stems from the fact that the statistical description of uncertain variables may not be well known or even not suitable. For example, in some cases, only a small number of measurements is available and the resulting errors are due to analog-digital conversion, modelling ap­ proximation or round-off, so that a statistical description may actually be unreliable. The interest in unknown but bounded setting is certainly not new. In fact, en­ gineering practice demands for appropriate algorithms in dealing with finite sample properties, finite parameter variations, tolerance analysis, etc. Despite the natural need for such methods, the lack of sufficiently well assessed theoretical results and algorithms prevented a systematic use of these procedures until recent years. How­ ever, in the last few years, important advances have been made both in estimation theory and in stability analysis.


Italy Natural Statistica Volume algorithms boundary element method control conversion modeling motivation paper performance stability tolerance value-at-risk

Editors and affiliations

  • M. Milanese
    • 1
  • R. Tempo
    • 1
  • A. Vicino
    • 2
  1. 1.Turin PolytechnicTurinItaly
  2. 2.University of FlorenceFlorenceItaly

Bibliographic information