State Estimation and Control of Conditionally Linear Systems,

Abstract

The filtering problem for a partially observable stochastic system, with linear in observable states dynamics and non-Gaussian initial conditions is studied here. It is shown that the conditional expected value of the unobservable states, given the past observations, can be expressed in terms of a finite dimensional set of statistics. This result, which generalizes the conditionally Gaussian filter is used to derive a separation principle for a linear-quadratic control problem. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1984
Accession Number
ADA142455

Entities

People

  • R. R. Mohler
  • W. J. Kolodziej

Organizations

  • Oregon State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Differential Equations
  • Distribution Functions
  • Equations
  • Filters
  • Filtration
  • Gaussian Distributions
  • Gaussian Processes
  • Linear Systems
  • Observation
  • Probability
  • Random Variables
  • Riccati Equation
  • Statistics
  • Stochastic Control
  • Stochastic Processes
  • Three Dimensional
  • Two Dimensional

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.