STOCHASTIC OPTIMAL CONTROL WITH IMPERFECTLY KNOWN PLANT DISTURBANCES,
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)
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 15, 1969
- Accession Number
- AD0698861
Entities
People
- Tzyh Jong Tarn
Organizations
- University of Washington