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Kalman Randomized Joint UKF Algorithm for Dual Estimation of States and Parameters in a Nonlinear System
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 Title & Authors
Kalman Randomized Joint UKF Algorithm for Dual Estimation of States and Parameters in a Nonlinear System
Safarinejadian, Behrouz; Vafamand, Navid;
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This article presents a new nonlinear joint (state and parameter) estimation algorithm based on fusion of Kalman filter and randomized unscented Kalman filter (UKF), called Kalman randomized joint UKF (KR-JUKF). It is assumed that the measurement equation is linear. The KRJUKF is suitable for time varying and severe nonlinear dynamics and does not have any systematic error. Finally, joint-EKF, dual-EKF, joint-UKF and KR-JUKF are applied to a CSTR with cooling jacket, in which production of propylene glycol happens and performance of KR-JUKF is evaluated.
Joint estimation;Kalman randomized joint UKF;Parameter estimation;CSTR;
 Cited by
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