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Published in:
Introduction to Adaptive Control Read chapter Read first chapter

2011 | OriginalPaper | Chapter

5. Recursive Plant Model Identification in Open Loop

Authors : Prof. Ioan Doré Landau, Prof. Rogelio Lozano, Prof. Mohammed M’Saad, Prof. Alireza Karimi

Published in: Adaptive Control

Publisher: Springer London

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Abstract

Plant model identification in open loop is a preliminary step for building an adaptive control system. Using the parameter adaptation algorithms presented in Chaps. 3 and 4 as well as the predictor structures presented in Chap. 2, one can develop recursive identification methods. The chapter presents a number of recursive identification methods and the associated model validation techniques. The problems of input design and model order selection are also addressed. The methodology is illustrated by the identification of a flexible transmission.

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previous chapter Parameter Adaptation Algorithms—Stochastic Environment
next chapter Adaptive Prediction
Footnotes
1
We will often call them recursive identification methods (algorithms).
 
2
Routines corresponding to these methods in Matlab and Scilab can be downloaded from the websites: http://​www.​landau-adaptivecontrol.​org and http://​landau-bookic.​lag.​ensieg.​inpg.​fr.
 
3
Routines corresponding to this method in Matlab and Scilab can be downloaded from the websites: http://​www.​landau-adaptivecontrol.​org and http://​landau-bookic.​lag.​ensieg.​inpg.​fr.
 
4
Conversely, for Gaussian data, uncorrelation implies independence. In this case, RN(i)=0,i≥1 implies independence between ε(t),ε(t−1),… , i.e., the sequence of residuals {ε(t)} is a Gaussian white noise.
 
5
Routines corresponding to these methods in Matlab and Scilab can be downloaded from the websites: http://​www.​landau-adaptivecontrol.​org and http://​landau-bookic.​lag.​ensieg.​inpg.​fr.
 
6
Routines corresponding to this method in Matlab and Scilab can be downloaded from the websites: http://​www.​landau-adaptivecontrol.​org and http://​landau-bookic.​lag.​ensieg.​inpg.​fr.
 
7
Routines for generating PRBS can be downloaded from the websites: http://​www.​landau-adaptivecontrol.​org and http://​landau-bookic.​lag.​ensieg.​inpg.​fr.
 
8
Routines corresponding to this method in Matlab and Scilab can be downloaded from the websites: http://​www.​landau-adaptivecontrol.​org and http://​landau-bookic.​lag.​ensieg.​inpg.​fr.
 
Literature
Adaptech (1988) WimPim + (includes, WinPIM, WinREG and WinTRAC) system identification and control software. User’s manual. 4, rue du Tour de l’Eau, 38400 St. Martin-d’Hères, France
Banon G, Aguilar-Martin J (1972) Estimation linéaire récurrente des paramètres des processus dynamiques soumis à des perturbations aléatoires. Rev CETHEDEC 9:38–86 MathSciNet
Bethoux G (1976) Approche unitaire des méthodes d’identification et de commande adaptative des procédés dynamiques. Thèse 3ème cycle, Institut National Polytechnique de Grenoble
Dugard L, Goodwin GC (1985) Global convergence of Landau’s “output error with adjustable compensator” adaptive algorithm. IEEE Trans Autom Control AC-30:593–595 MathSciNetCrossRef
Duong HG, Landau ID (1994) On statistical properties of a test for model structure selection using the extended instrumental variable approach. IEEE Trans Autom Control AC-39:211–215 MathSciNetCrossRef
Landau ID (1979) Adaptive control—the model reference approach. Marcel Dekker, New York MATH
Landau ID (1990a) Algorithmes d’adaptation paramétrique. In: Dugard L, Landau ID (eds) Ecole d’Eté d’Automatique, LAG, Grenoble
Ljung L (1999) System identification: theory for the user, 2nd edn. Prentice-Hall, Englewood Cliffs
Ljung L, Söderström T (1983) Theory and practice of recursive identification. MIT Press, Cambridge MATH
Söderström T, Stoica P (1989) System identification. Prentice-Hall, New York MATH
Young PC (1969) An instrumental variable method for real time identification of a noisy process. Automatica 66:271–288
Metadata
Title
Recursive Plant Model Identification in Open Loop
Authors
Prof. Ioan Doré Landau
Prof. Rogelio Lozano
Prof. Mohammed M’Saad
Prof. Alireza Karimi
Copyright Year
2011
Publisher
Springer London
Book
Adaptive Control

Print ISBN: 978-0-85729-663-4

Electronic ISBN: 978-0-85729-664-1

Copyright Year: 2011

DOI
https://doi.org/10.1007/978-0-85729-664-1_5