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Identification and Control Using Volterra Models

  • F. J. DoyleIII
  • R. K. Pearson
  • B. A. Ogunnaike

Part of the Communications and Control Engineering book series (CCE)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 1-15
  3. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 17-45
  4. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 47-78
  5. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 79-103
  6. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 105-162
  7. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 163-177
  8. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 179-195
  9. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 197-216
  10. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 217-285
  11. F. J. Doyle III, R. K. Pearson, B. A. Ogunnaike
    Pages 287-293
  12. Back Matter
    Pages 295-314

About this book

Introduction

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.

Keywords

Volterra models electrical engineering identification model modeling nonlinear nonlinear control

Authors and affiliations

  • F. J. DoyleIII
    • 1
  • R. K. Pearson
    • 2
  • B. A. Ogunnaike
    • 3
  1. 1.Department of Chemical EngineeringUniversity of DelawareNewarkUSA
  2. 2.Instutut fuer AutomatikETH ZurichZurichSwitzerland
  3. 3.DuPont CompanyWilmingtonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-0107-9
  • Copyright Information Springer-Verlag London Limited 2002
  • Publisher Name Springer, London
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4471-1063-7
  • Online ISBN 978-1-4471-0107-9
  • Series Print ISSN 0178-5354
  • Buy this book on publisher's site
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