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CDC
2009
IEEE

Further results on plant parameter identification using continuous-time multiple-model adaptive estimators

11 years 9 months ago
Further results on plant parameter identification using continuous-time multiple-model adaptive estimators
This paper describes a deterministic approach to adaptive state and parameter estimation using a multiple model structure. In the set-up adopted, the plant of interest is described by a finite dimensional model with parametric uncertainty. To each choice of a finite number of parameter values there corresponds a finite set of multiple design models and a corresponding set of observers. Assuming the latter have been chosen, a Dynamic Weighting Signal Generator (DWSG) performs on-line adaptation of the weights given to the individual observer estimates based on the energy of the output error signals. In the present paper we develop a distance-like pseudo norm between the true plant and the identified model in a deterministic setting, based on the energy of the output error signals. Furthermore we show, under a distinguishability condition, that the model identified is the one that is closest to the true plant in the defined deterministic norm. We also prove that the convergence of the pa...
Vahid Hassani, A. Pedro Aguiar, António Man
Added 12 Aug 2010
Updated 12 Aug 2010
Type Conference
Year 2009
Where CDC
Authors Vahid Hassani, A. Pedro Aguiar, António Manuel Santos Pascoal, Michael Athans
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