Accession Number:

AD0736799

Title:

Bounds on the Accuracy in Causal Filtering for Nonlinear Observations with Some Implications on Asymptotic Separation in Stochastic Control,

Descriptive Note:

Corporate Author:

WASHINGTON UNIV ST LOUIS MO CONTROL SYSTEMS SCIENCE AND ENGINEERING

Personal Author(s):

Report Date:

1971-06-30

Pagination or Media Count:

15.0

Abstract:

A bound is derived on the accuracy in causally estimating a Gaussian process from nonlinear observations. Both additive Gaussian noise and Poisson observations are included. The bound is used to study the control of a stochastic linear dynamical system with nonlinear observations and an average quadratic cost. An asymptotic separation theorem is established showing that a linear feedback control law, involving a state estimate, is asymptotically optimum as the accuracy of the state estimate approaches the bound. Author

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE