
Accession Number : ADA189720
Title : The Adjoint Process in Stochastic Optimal Control.
Descriptive Note : Rept. for 30 Sep 8630 Sep 87,
Corporate Author : ALBERTA UNIV EDMONTON DEPT OF STATISTICS AND APPLIED PROBABILITY
Personal Author(s) : Elliott, Robert J ; Kohlmann, Michael
PDF Url : ADA189720
Report Date : 11 Nov 1987
Pagination or Media Count : 17
Abstract : The focus of this research is the filtering jump processes. To investigate the filtering of manifold valued processes, their approximation by random walks and Markov chains was studied. The object was to approximate a signal process by a finite state jump process for which a finite dimensional filter is available. Four papers were published during the past year, including The existence of smooth densities for the prediction, filtering and smoothing problems and The partially observed stochastic minimum principle. Using stochastic flows a minimum principle is obtained when a diffusion is controlled using stochastic open loop controls. An equation for the adjoint process is then derived using an explicit formula for the integrand in a certain stochastic integral.
Descriptors : *OPTIMIZATION, *STOCHASTIC CONTROL, DENSITY, FLOW, MARKOV PROCESSES, OPEN LOOP SYSTEMS, SIGNAL PROCESSING, SIZES(DIMENSIONS), STOCHASTIC PROCESSES, MATHEMATICAL FILTERS, DIFFERENTIAL EQUATIONS
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE