Title :
On approximation techniques for stochastic control with partial information
Author_Institution :
Univ. Paris-Dauphine, France
Abstract :
Finite-dimensional filters are used in the context of stochastic control with partial information to obtain a kind of approximate separation principle. It turns out that many technical problems are met in the study of the approximation and that some simplification is desirable. The author shows how to use partial differential equation techniques to simplify the proofs as much as possible and to permit more general classes of approximate feedback to be envisioned
Keywords :
filtering and prediction theory; partial differential equations; stochastic systems; approximate separation principle; approximation techniques; finite dimensional filters; partial differential equation; partial information; stochastic control; Cost function; Covariance matrix; Feedback; Maximum likelihood detection; Nonlinear filters; Probability distribution; Process control; Random variables; Stochastic processes; Stochastic resonance;
Conference_Titel :
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location :
Tampa, FL
DOI :
10.1109/CDC.1989.70210
