Reference:
Zs. Lendek, R. Babuška, and B. De Schutter, "State estimation under uncertainty: A survey," Tech. report 06-004, Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands, 65 pp., Feb. 2006.Abstract:
This report gives an overview of the state-of-the-art in state estimation under uncertainty. More specifically, we discuss two probabilistic state estimation methods: Kalman filters and particle filters, and several types of fuzzy and neural observers.Bibtex entry: