Nearly Optimal State Feedback Controls for Stochastic Systems with Wideband Noise Disturbances.

Abstract

Much of optimal stochastic control theory is concerned with diffusion models. Such models are often only idealizations (or limits in an appropriate sense) of the actual physical process, which might be driven by a wide bandwidth (not white) process or be a discrete parameter system with correlated driving noises. Optimal or nearly optimal controls, derived for the diffusion models, would not normally be useful or even of much interest, if they were not also 'nearly optimal' for the physical system which the diffusion approximates. It turns out that, under quite broad conditions, the 'nearly optimal' controls for the diffusions do have this desired robustness property and are 'nearly optimal' for the physical (say wide band noise driven) process, even when compared to controls which can depend on all the (past) driving noise. The authors treat the problem over a finite time interval, as well as the average cost per unit time problem. Extensions to discrete parameter systems, and to systems stopped on first exit from a bounded domain are also discussed. Weak convergence methods provide the appropriate analytical tools.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1985
Accession Number
ADA162271

Entities

People

  • Harold J. Kushner
  • W. Runggaldier

Organizations

  • Brown University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Applied Mathematics
  • Continuity
  • Convergence
  • Diffusion
  • Feedback
  • Intervals
  • Markov Chains
  • Markov Processes
  • Numbers
  • Probability
  • Random Variables
  • Sequences
  • Stationary Processes
  • Theorems
  • Topology
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Fluid Dynamics.
  • Operations Research
  • Systems Analysis and Design