Modeling of Complex Adaptive Systems in Air Operations

Abstract

This report introduces the concept of using simulation for both plan tracking and state estimation and prediction. Model predictive control theory provides the basis for this investigation. Given some set of objectives the military commander must devise a sequence of actions that transform the current state to the desired one. The desire to do this in faster than real-time so that many courses of action can be considered motivates us to investigate modeling techniques that explicitly produce such courses of action. The class of problem can be modeled as a Markov decision process (MDP) whose principal solution is stochastic dynamic programming. The report presents a historical context for the application of control theory to the command and control problem space and introduces a mechanism for dealing with the resulting computational complexity.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2006
Accession Number
ADA457738

Entities

People

  • Dawn A. Trevisani
  • Timothy E. Busch

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Cyber
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Adaptive Systems
  • Aircrafts
  • Artificial Intelligence
  • Command And Control
  • Command And Control Systems
  • Computational Complexity
  • Computer Programming
  • Control Systems
  • Databases
  • Dynamic Programming
  • Information Systems
  • Model Predictive Control
  • Operating Systems
  • Operations Research
  • Situational Awareness
  • Unmanned Aerial Vehicles
  • War Colleges

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Systems Analysis and Design

Technology Areas

  • Fully Networked C3
  • Fully Networked C3 - Command and Control
  • Space
  • Space - Spacecraft Maneuvers