Block-oriented Nonlinear System Identification

  • Fouad Giri
  • Er-Wei Bai

Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 404)

Table of contents

  1. Front Matter
  2. Block-oriented Nonlinear Models

  3. Iterative and Overparameterization Methods

  4. Stochastic Methods

  5. Frequency Methods

    1. Front Matter
      Pages 159-159
    2. Fouad Giri, Youssef Rochdi, Jean-Baptiste Gning, Fatima-Zahra Chaoui
      Pages 181-207
  6. SVM, Subspace and Separable Least-squares

    1. Front Matter
      Pages 227-227
    2. Jan-Willem van Wingerden, Michel Verhaegen
      Pages 229-239
    3. Ivan Goethals, Kristiaan Pelckmans, Tillmann Falck, Johan A. K. Suykens, Bart De Moor
      Pages 241-258
  7. Blind Methods

    1. Front Matter
      Pages 271-271
    2. Jiandong Wang, Akira Sano, Tongwen Chen, Biao Huang
      Pages 293-312
  8. Decoupling Inputs and Bounded Error Methods

    1. Front Matter
      Pages 333-333
    2. Youssef Rochdi, Vincent Van Assche, Fatima-Zahra Chaoui, Fouad Giri
      Pages 347-365
    3. Vito Cerone, Dario Piga, Diego Regruto
      Pages 367-382
  9. Application of Block-oriented Models

  10. Back Matter

About this book


Block-oriented Nonlinear System Identification deals with an area of research that has been very active since the turn of the millennium. The book makes a pedagogical and cohesive presentation of the methods developed in that time. These include:

• iterative and over-parameterization techniques;

• stochastic and frequency approaches;

• support-vector-machine, subspace, and separable-least-squares methods;

• blind identification method;

• bounded-error method; and

• decoupling inputs approach.

The identification methods are presented by authors who have either invented them or contributed significantly to their development. All the important issues e.g., input design, persistent excitation, and consistency analysis, are discussed. The practical relevance of block-oriented models is illustrated through biomedical/physiological system modeling. The book will be of major interest to all those who are concerned with nonlinear system identification whatever their activity areas. This is particularly the case for educators in electrical, mechanical, chemical and biomedical engineering and for practising engineers in process, aeronautic, aerospace, robotics and vehicles control. Block-oriented Nonlinear System Identification serves as a reference for active researchers, newcomers, industrial and education practitioners and graduate students alike.


Block-orientated Systems Control Cross000 Hammerstein Nonlinear Systems Nonlinear system Parameter Estimation Systems Identification Wiener system system identification

Editors and affiliations

  • Fouad Giri
    • 1
  • Er-Wei Bai
    • 2
  1. 1.Laboratoire GREYCEnsicaenCaen CedexFrance
  2. 2.Seamans Center for the Engineering Arts and SciencesThe University of IowaIowa CityUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag London 2010
  • Publisher Name Springer, London
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-1-84996-512-5
  • Online ISBN 978-1-84996-513-2
  • Series Print ISSN 0170-8643
  • Series Online ISSN 1610-7411
  • Buy this book on publisher's site