COMPARISON OF STATE ESTIMATION TECHNIQUES, APPLIED TO A BIOLOGICAL WASTEWATER TREATMENT PROCESS

In this paper the problem of optimal state estimation in a biological wastewater treatment process (WWTP) is considered. The standard Kalman filter (KF) and its extensions: the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are used to estimate the unmeasured state. The prediction of the state with the standard KF is poor due to the high nonlinearity of the biological WWTP. Thus, the nonlinear estimation approaches are focused, with a comparison between the EKF and the UKF. The simulation results show that the UKF provides slightly better state estimate than the EKF for both an observable process and an unobservable process.