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Convergent iterative model unfalsification for control

Convergent iterative model unfalsification for control
Convergent iterative model unfalsification for control
Iterative controller design by model unfalsification and robust controller design is reexamined and developed further from [7]. Two frecuency dependent uncertainty functions are used to ease the process of modelling for control. One is the maximum allowed gain errors (AGE) of a nominal plant which depends on the controller, nominal model and the stability robustness requirement. The other functions used are frecuency dependent unfalsified lower bounds of plant dynamical uncertainty around nominal models.
The controller is called feasible if the allowed plant perturbation function bounds an estimated plant uncertainty for each frecuency. If there is no feasible controller then more experiments are carried out with the same controller which excite the plant at the "offending frecuencies". Otherwise the feasible controller with the largest stability margin and "most promising" performance is used in the next experiment with the testing input spectrum focusing on the frecuencies where the stability margin is small and the performance is sensitive.
4221-4226
Veres, Sandor M.
909c60a0-56a3-4eb6-83e4-d52742ecd304
Veres, Sandor M.
909c60a0-56a3-4eb6-83e4-d52742ecd304

Veres, Sandor M. (2002) Convergent iterative model unfalsification for control. 41st IEEE Conference on Decision and Control, Las Vegas, Nevada, United States. 10 - 13 Dec 2002. pp. 4221-4226 .

Record type: Conference or Workshop Item (Paper)

Abstract

Iterative controller design by model unfalsification and robust controller design is reexamined and developed further from [7]. Two frecuency dependent uncertainty functions are used to ease the process of modelling for control. One is the maximum allowed gain errors (AGE) of a nominal plant which depends on the controller, nominal model and the stability robustness requirement. The other functions used are frecuency dependent unfalsified lower bounds of plant dynamical uncertainty around nominal models.
The controller is called feasible if the allowed plant perturbation function bounds an estimated plant uncertainty for each frecuency. If there is no feasible controller then more experiments are carried out with the same controller which excite the plant at the "offending frecuencies". Otherwise the feasible controller with the largest stability margin and "most promising" performance is used in the next experiment with the testing input spectrum focusing on the frecuencies where the stability margin is small and the performance is sensitive.

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More information

Published date: 2002
Venue - Dates: 41st IEEE Conference on Decision and Control, Las Vegas, Nevada, United States, 2002-12-10 - 2002-12-13

Identifiers

Local EPrints ID: 22002
URI: http://eprints.soton.ac.uk/id/eprint/22002
PURE UUID: e80a085e-cc6e-43e3-863d-59caffea6dca

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Date deposited: 02 Jun 2006
Last modified: 06 Oct 2020 23:43

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