Efficient minimal disturbance estimation in estimation based multiple model switched adaptive control
Efficient minimal disturbance estimation in estimation based multiple model switched adaptive control
This paper addresses the problem of efficiently solving the minimal disturbance estimation problems in Estimation based Multiple Model Switched Adaptive Control (EMMSAC) for a large set of linear time-invariant candidate plant models. We show that it is possible to approximate the minimal disturbance measure functional of any member in the original set by only using the minimal disturbance measure functionals for a basic candidate plant models set chosen from the original set via a bank of low-pass, high-pass, and band-pass filters. We also analyse the efficiency of the proposed method.
efficient minimal disturbance estimation, multiple model switched adaptive control, kalman filter, filter bank
1-24
Liu, Jing
a3428c79-3f08-43ab-9f64-ec895d5e6cba
French, Mark
22958f0e-d779-4999-adf6-2711e2d910f8
Liu, Jing
a3428c79-3f08-43ab-9f64-ec895d5e6cba
French, Mark
22958f0e-d779-4999-adf6-2711e2d910f8
Liu, Jing and French, Mark
(2014)
Efficient minimal disturbance estimation in estimation based multiple model switched adaptive control.
IEEE Transactions on Automatic Control, .
(Submitted)
Abstract
This paper addresses the problem of efficiently solving the minimal disturbance estimation problems in Estimation based Multiple Model Switched Adaptive Control (EMMSAC) for a large set of linear time-invariant candidate plant models. We show that it is possible to approximate the minimal disturbance measure functional of any member in the original set by only using the minimal disturbance measure functionals for a basic candidate plant models set chosen from the original set via a bank of low-pass, high-pass, and band-pass filters. We also analyse the efficiency of the proposed method.
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Submitted date: 2014
Keywords:
efficient minimal disturbance estimation, multiple model switched adaptive control, kalman filter, filter bank
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 363498
URI: http://eprints.soton.ac.uk/id/eprint/363498
ISSN: 0018-9286
PURE UUID: f76d4a3e-7e77-491d-909a-2184320bb470
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Date deposited: 25 Mar 2014 14:52
Last modified: 11 Dec 2021 03:55
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Author:
Jing Liu
Author:
Mark French
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