Accession Number:

AD0698861

Title:

STOCHASTIC OPTIMAL CONTROL WITH IMPERFECTLY KNOWN PLANT DISTURBANCES,

Descriptive Note:

Corporate Author:

WASHINGTON UNIV ST LOUIS MO CONTROL SYSTEMS SCIENCE AND ENGINEERING

Personal Author(s):

Report Date:

1969-10-15

Pagination or Media Count:

10.0

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

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE