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    Joint state and parameter estimation for a class of cascade systems: Application to a hemodynamic model

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    Type
    Conference Paper
    Authors
    Zayane, Chadia cc
    Liu, Dayan
    Laleg-Kirati, Taous-Meriem cc
    KAUST Department
    Applied Mathematics and Computational Science Program
    Computational Bioscience Research Center (CBRC)
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2014-06
    Permanent link to this record
    http://hdl.handle.net/10754/564926
    
    Metadata
    Show full item record
    Abstract
    In this paper, we address a special case of state and parameter estimation, where the system can be put on a cascade form allowing to estimate the state components and the set of unknown parameters separately. Inspired by the nonlinear Balloon hemodynamic model for functional Magnetic Resonance Imaging problem, we propose a hierarchical approach. The system is divided into two subsystems in cascade. The state and input are first estimated from a noisy measured signal using an adaptive observer. The obtained input is then used to estimate the parameters of a linear system using the modulating functions method. Some numerical results are presented to illustrate the efficiency of the proposed method.
    Citation
    Zayane-Aissa, C., Liu, D.-Y., & Laleg-Kirati, T.-M. (2014). Joint state and parameter estimation for a class of cascade systems: Application to a hemodynamic model. 2014 European Control Conference (ECC). doi:10.1109/ecc.2014.6862585
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2014 European Control Conference (ECC)
    Conference/Event name
    13th European Control Conference, ECC 2014
    ISBN
    9783952426913
    DOI
    10.1109/ECC.2014.6862585
    ae974a485f413a2113503eed53cd6c53
    10.1109/ECC.2014.6862585
    Scopus Count
    Collections
    Conference Papers; Applied Mathematics and Computational Science Program; Electrical and Computer Engineering Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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