Direct identification of continuous-time linear parameter-varying input/output models
Direct identification of continuous-time linear parameter-varying input/output models
- Author(s): V. Laurain ; R. Tóth ; M. Gilson ; H. Garnier
- DOI: 10.1049/iet-cta.2010.0218
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- Author(s): V. Laurain 1 ; R. Tóth 2 ; M. Gilson 1 ; H. Garnier 1
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View affiliations
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Affiliations:
1: Centre de Recherche en Automatique de Nancy (CRAN), Nancy-Université, CNRS, France
2: Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands
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Affiliations:
1: Centre de Recherche en Automatique de Nancy (CRAN), Nancy-Université, CNRS, France
- Source:
Volume 5, Issue 7,
5 May 2011,
p.
878 – 888
DOI: 10.1049/iet-cta.2010.0218 , Print ISSN 1751-8644, Online ISSN 1751-8652
Controllers in the linear parameter-varying (LPV) framework are commonly designed in continuous time (CT) requiring accurate and low-order CT models of the system. However, identification of CT-LPV models is largely unsolved, representing a gap between the available LPV identification methods and the needs of control synthesis. In order to bridge this gap, direct identification of CT-LPV systems in an input–output setting is investigated, focusing on the case when the noise part of the data generating system is an additive discrete-time (DT) coloured noise process. To provide consistent model parameter estimates in this setting, a refined instrumental variable (IV) approach is proposed and its properties are analysed based on the prediction-error framework. The benefits of the introduced direct CT-IV approach over identification in the DT case are demonstrated through a representative simulation example inspired by the Rao–Garnier benchmark.
Inspec keywords: discrete time systems; identification; continuous time systems; control system synthesis
Other keywords:
Subjects: Simulation, modelling and identification; Control system analysis and synthesis methods; Discrete control systems
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