Applying a cubature Kalman filter for the nonlinear state estimations of a continuous stirred tank reactor

Applying cubature Kalman filter(CKF) to the nonlinear state estimations of continuous stirred tank reactor (CSTR) whose process exhibits strongly nonlinear and high dimensions is proposed in this paper. Moreover, the main contribution of this paper is to show the efficacy of CKF in comparison with extended Kalman filter(EKF) and scaled unscented Kalman filter(SUKF) in terms of calculation speed and estimate accuracy within two studies which are normal operating conditions and changing parameters conditions. The estimate effect of the states is demonstrated by conducting simulation studies on a CSTR which has been dynamically simulated. Simulation results show that designing the observer by CKF approach not only can realize more reliable state estimation, but also has the main advantage of lower operation time for both cases.