Title :
Recursive algorithms for identification in closed loop-a unified approach and evaluation
Author :
Landau, I.D. ; Karimi, A.
Author_Institution :
Lab. d´´Autom. de Grenoble, ENSIEG, St. Martin d´´Heres, France
Abstract :
A unified presentation of recursive algorithms for plant model identification in closed loop is given. From the basic formulation of the problem of finding the plant model which gives the best predictor for the closed loop system the two families of algorithms using either a reparameterized predictor for the closed loop or a plant predictor operating on filtered data are presented and their asymptotic properties are examined. Validation tests for the models identified in closed loop are proposed
Keywords :
closed loop systems; filtering theory; modelling; poles and zeros; prediction theory; recursive estimation; transfer functions; asymptotic properties; closed loop identification; closed loop system; plant model identification; plant predictor; recursive algorithms; reparameterized predictor; validation tests; Asymptotic stability; Closed loop systems; Context modeling; Digital control; Open loop systems; Parameter estimation; Predictive models; Robust control; Stochastic processes; Testing;
Conference_Titel :
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-3590-2
DOI :
10.1109/CDC.1996.572705
