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
- 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
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.

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Direct identification of continuous-time linear parameter-varying input/output models

Direct identification of continuous-time linear parameter-varying input/output models

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