Title :
A convergence condition for optimal nonlinear filtering for systems with unknown parameters
Author :
Casiello, Francisco A. ; Loparo, Kenneth A.
Author_Institution :
Dept. of Syst. Eng., Case Western Reserve Univ., Cleveland, OH, USA
Abstract :
An examination is made of the problem of estimating the state of linear stochastic plant with unknown parameters taking values in a finite set. Stochastic stability theory is used to establish conditions under which the a posteriori probabilities defined on a finite parameter set converge almost surely, both in continuous and discrete time. An example of what happens if the conditions are not satisfied is given
Keywords :
convergence; filtering and prediction theory; optimisation; state estimation; stochastic systems; a posteriori probabilities; continuous-time systems; convergence condition; discrete-time systems; linear system; optimal nonlinear filtering; stability; state estimation; stochastic system; unknown parameters; Convergence; Covariance matrix; Differential equations; Filtering; Probability distribution; Stability; State estimation; Stochastic processes; Stochastic systems; Systems engineering and theory;
Conference_Titel :
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Conference_Location :
Austin, TX
DOI :
10.1109/CDC.1988.194680
