شماره ركورد كنفرانس :
5048
عنوان مقاله :
Sensor Fault Detection of a Highly Nonlinear CSTR Plant Using an Unscented Kalman Filter
Author/Authors :
Jafar ،Zarei Iran University of Science & Technology , Javad ،Poshtan Iran University of Science & Technology
كليدواژه :
Nonlinear dynamics , Simulation , Nonlinear state estimation , Extended Kalman filter , Unscented filter
عنوان كنفرانس :
ششمين كنگره بين المللي مهندسي شيمي
چكيده لاتين :
In this paper, we propose an unscented Kalman filter (UKF) algorithm, as an alternative to the Extended Kalman Filter
(EKF) for nonlinear processes fault detection. Although effectiveness of the EKF has been widely recognized, the
practical applications of EKFs are still very limited. This is due to the fact that the estimates of EKF are often biased.
Unscented filter is a new generalization of the Kalman filter for state estimation of nonlinear systems. In order to
evaluate its ability, the presented method is applied to a highly nonlinear dynamic system describing the behavior of a
non-adiabatic CSTR. The faulty behavior of output sensors in the chemical reactor is investigated. Simulation results
show the efficiency and performance of the presented method.