CUED Publications database

Worst case identification using FIR models

Date, P and Vinnicombe, G (2015) Worst case identification using FIR models. In: UNSPECIFIED pp. 1270-1275..

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This paper considers a robustly convergent algorithm for worst case identification using FIR models. A new and stronger notion of robust convergence is established, and error bounds are obtained for a fixed model order as the length of data tends to infinity. The algorithm is shown to be implementable as a solution to an LMI optimisation problem. A robustly convergent algorithm for identification of plant coprime factors is suggested. An iterative technique for identification in the ν-gap metric is given. Two simulation examples demonstrate the use of these algorithms.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div F > Control
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:43
Last Modified: 02 Sep 2021 04:58
DOI: doi:10.23919/ecc.1999.7099485