Accession Number : AD0736799

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

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

Personal Author(s) : Snyder,Donald L. ; Rhodes,Ian B.

Report Date : 30 JUN 1971

Pagination or Media Count : 15

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)

Descriptors :   (*ADAPTIVE CONTROL SYSTEMS, MATHEMATICAL MODELS), STOCHASTIC PROCESSES, NONLINEAR SYSTEMS, ASYMPTOTIC SERIES, NUMERICAL ANALYSIS, THEOREMS

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE