Title :
Optimal state estimation of singular stochastic systems
Author :
P. Zampa;R. Arnost
Author_Institution :
Dept. of Cybern., Univ. of West Bohemia, Plzen, Czech Republic
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper deals with optimal state estimation problem of both singular and especially non-singular stochastic causal systems solution of which is based on recently submitted new approach to system theory. The solution to so important a task is well known as the Kalman filtering. However, some surprisingly serious problems arise in case of stochastic system with singular uncertainty in the continuous-time domain. The presented solution transforms, according to the new approach to system theory, the original problem into the discrete-time domain whereupon the optimal discrete-time Kalman filter can be designed. In regard of the given continuous-time problem, the obtained estimator is to be transformed from the discrete-time to the continuous-time domain. Such a transformation procedure is called the continualisation process. The solution leads to utilization of backward derivatives.
Keywords :
"State estimation","Stochastic systems","Riccati equations","Cybernetics","Uncertainty","Stochastic processes","Kalman filters","Filtering","Discrete transforms","White noise"
Conference_Titel :
Automation Congress, 2002 Proceedings of the 5th Biannual World
Print_ISBN :
1-889335-18-5
DOI :
10.1109/WAC.2002.1049480