Controller validation based on an identified model

Author

Bombois, Xavier ; Gevers, Michel ; Scorletti, GQard

Author_Institution

CESAME, Univ. Catholique de Louvain, Belgium

Volume

3

fYear

1999

fDate

1999

Firstpage

2816

Abstract

This paper focuses on the validation of a controller that has been designed from an unbiased model of the true system, identified either in open-loop or in closed-loop using a prediction error framework. A controller is said to be validated if it stabilizes all models in a parametric uncertainty set containing the parameters of the true system with some prescribed probability. This uncertainty set is deduced from the covariance matrix of the parameters of the identified model. Our contribution is to embed this set in the smallest possible overbounding coprime factor uncertainty set. This then allows us to use the results of mainstream robust control theory such as the Vinnicombe gap between plants and its related stability theorems

Keywords

closed loop systems; control system synthesis; covariance matrices; identification; probability; robust control; Vinnicombe gap; closed-loop system; controller validation; covariance matrix; open-loop system; overbounding coprime factor uncertainty; parametric uncertainty set; prediction error framework; probability; robust control theory; stability; unbiased model; Additives; Covariance matrix; Ellipsoids; Error correction; Frequency; Open loop systems; Predictive models; Robust control; Robust stability; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1999. Proceedings of the 38th IEEE Conference on

Conference_Location

Phoenix, AZ

ISSN

0191-2216

Print_ISBN

0-7803-5250-5

Type

conf

DOI

10.1109/CDC.1999.831360

Filename

831360