One-step ahead Prediction for Parameter Estimation in Physiological Hybrid Models
| Authors: | van Riel Natal, Eindhoven University of Technology, Netherlands
Juloski Aleksandar, Eindhoven University of Technology, Netherlands
op den Buijs Jorn, Eindhoven University of Technology, Netherlands |
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| Topic: | 8.2 Modelling & Control of Biomedical Systems |
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| Session: | Parameter Estimation and Kinetic Modelling I |
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| Keywords: | hybrid models, identification algorithms, least-squares identification, parameter estimation, physiological models, prediction error methods |
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Abstract
Identification of hybrid systems is complex because it is not a priori known which data is generated by which discrete mode of the system. A novel procedure is presented for the simultaneous determination of the model parameters and classification of the data. Initial parameter estimates are obtained based on a priori knowledge of the modes of the system. Next, the data points are subsequently classified and with each new classified data point the parameter estimates are refined. The proposed procedure is applied in the estimation of parameters in a hybrid description of calcium cycling in the intact heart.
