Accession Number : AD0698861

Title :   STOCHASTIC OPTIMAL CONTROL WITH IMPERFECTLY KNOWN PLANT DISTURBANCES,

Corporate Author : WASHINGTON UNIV ST LOUIS MO CONTROL SYSTEMS SCIENCE AND ENGINEERING

Personal Author(s) : Tarn,Tzyh Jong

Report Date : 15 OCT 1969

Pagination or Media Count : 10

Abstract : It is the purpose of this correspondence to show how filtering theory based on a Bayesian approach may be used to solve the problem of optimally controlling a linear discrete stochastic system in which the additive Gaussian plant noise has fixed but unknown variance. Selecting a reproducible type of probability density and applying dynamic programming, an exact analytical solution of the feedback control law may be found. (Author)

Descriptors :   (*ADAPTIVE CONTROL SYSTEMS, STOCHASTIC PROCESSES), INFORMATION THEORY, DYNAMIC PROGRAMMING, ANALYSIS OF VARIANCE, OPTIMIZATION, FEEDBACK, THESES

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE