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Interactive System Identification: Prospects and Pitfalls

  • Book
  • © 1991

Overview

Authors:
  1. Torsten Bohlin

    1. Automatic Control, Royal Institute of Technology, Stockholm, Sweden

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

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Table of contents (10 chapters)

  1. Front Matter

    Pages I-XII
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  2. Introduction

    • Torsten Bohlin
    Pages 1-17

  3. Randomness, probability, and likelihood

    • Torsten Bohlin
    Pages 18-41

  4. The experiment

    • Torsten Bohlin
    Pages 42-74

  5. The identification problem

    • Torsten Bohlin
    Pages 75-110

  6. Modelling

    • Torsten Bohlin
    Pages 111-173

  7. Large-sample theory

    • Torsten Bohlin
    Pages 174-219

  8. Validation techniques

    • Torsten Bohlin
    Pages 220-243

  9. Falsification techniques

    • Torsten Bohlin
    Pages 244-290

  10. Structure identification

    • Torsten Bohlin
    Pages 291-329

  11. A unified design procedure

    • Torsten Bohlin
    Pages 330-341

  12. Back Matter

    Pages 342-365
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Keywords

About this book

The craft of designing mathematical models of dynamic objects offers a large number of methods to solve subproblems in the design, typically parameter estimation, order determination, validation, model reduc­ tion, analysis of identifiability, sensi tivi ty and accuracy. There is also a substantial amount of process identification software available. A typi­ cal 'identification package' consists of program modules that implement selections of solution methods, coordinated by supervising programs, communication, and presentation handling file administration, operator of results. It is to be run 'interactively', typically on a designer's 'work station' . However, it is generally not obvious how to do that. Using interactive identification packages necessarily leaves to the user to decide on quite a number of specifications, including which model structure to use, which subproblems to be solved in each particular case, and in what or­ der. The designer is faced with the task of setting up cases on the work station, based on apriori knowledge about the actual physical object, the experiment conditions, and the purpose of the identification. In doing so, he/she will have to cope with two basic difficulties: 1) The com­ puter will be unable to solve most of the tentative identification cases, so the latter will first have to be form11lated in a way the computer can handle, and, worse, 2) even in cases where the computer can actually produce a model, the latter will not necessarily be valid for the intended purpose.

Authors and Affiliations

  • Automatic Control, Royal Institute of Technology, Stockholm, Sweden

    Torsten Bohlin

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