Online estimation of the state and parameters in compartmental models using extended Kalman filter

In this paper, the ingestion and subsequent metabolism of a drug in a given individual, are investigated through the use of compartmental models. The extended Kalman filter (EKF) has been utilized to solve the resulting nonlinear estimation problem at the output of the compartments. The dependence of EKF's performance on the selection of appropriate values of the arbitrary matrices, the measurement covariance R and the process noise covariance e has been demonstrated in the simulations. With the appropriate choice of the matrices the EKF provides a very useful tool for online estimation of both the state and the parameters.