Constrained nonlinear state estimation based on the UKF approach

In this paper we investigate the use of an alternative to the extended Kalman filter (EKF), the unscented Kalman filter (UKF). First we give a broad overview of different UKF algorithms, then present an extension to the ensemble of UKF algorithms, and finally address the issue of how to add constraints using the UKF approach. The performance of the constrained approach is compared with EKF and a selection of UKF algorithms on nonlinear process systems with multimodal probability density functions. The conclusion is that with an algebraic reformulation of the correction part, the reformulated UKF shows strong performance on our selection of nonlinear constrained process systems.