Direct identification of continuous-time LPV models

V. Laurain, M. Gilson, R. Toth, H. Garnier

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)
148 Downloads (Pure)


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. Nonetheless, most of the methods dedicated to the identification of LPV systems are addressed in the discrete-time setting. In practice when discretizing models which are naturally expressed in CT, the dependency on the scheduling variables becomes non-trivial and over-parameterized. Consequently, direct identification of CT-LPV systems in an input-output setting is investigated. To provide consistent model parameter estimates in this setting, a refined instrumental variable approach is proposed. The statistical properties of this approach are demonstrated through a Monte Carlo simulation example.
Original languageEnglish
Title of host publicationProceedings of the American Control Conference, 29 June-1 July 2011, San Francisco, California
Publication statusPublished - 2011
Event2011 American Control Conference (ACC 2011), June 29 - July 1, 2011, San Francisco, CA, USA - San Francisco Hilton on O'Farrell Street, San Francisco, CA, United States
Duration: 29 Jun 20111 Jul 2011


Conference2011 American Control Conference (ACC 2011), June 29 - July 1, 2011, San Francisco, CA, USA
Abbreviated titleACC 2011
Country/TerritoryUnited States
CitySan Francisco, CA
Internet address


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