Simultaneous Design of Communication Strategies and Control Policies in Stochastic Systems

Abstract

This document considers the problem of simultaneously designing communication strategies and control policies in decentralized stochastic systems. Such problems are difficult to solve, mainly because of the nonclassical nature of their information structure. We have identified classes of such problems with linear dynamics, quadratic loss functionals and Gaussian statistics for which the optimality of linear strategies can be established. The general approach used consists of first finding a lower bound on the cost, and then constructing joint strategies that attain this lower bound. For some instances of the cases where linear strategies fail to provide globally optimal solutions, explicit nonlinear strategies are obtained that demonstrate the inferiority of linear designs. The problems studied in this thesis can be viewed as important prototype problems, which are essential building blocks for a general theory of multistage distributed decision making under nonclassical information, and possibly partial statistical description. Keywords: Stochastic control, Information theory.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1988
Accession Number
ADA199439

Entities

People

  • Rajesh C. Bansal

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Coding
  • Communication Channels
  • Communication Systems
  • Computational Complexity
  • Computer Programming
  • Computer Programs
  • Decoding
  • Electrical Engineering
  • Engineering
  • Information Science
  • Information Theory
  • Probability
  • Random Variables
  • Statistics
  • Stochastic Control
  • Theorems

Fields of Study

  • Engineering
  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms