Optimal And Adaptive Control of Stochastic Systems

Abstract

A major focus of the research of this grant has been the control of stochastic systems with a large family of noise processes that are important for modeling and that have not previously been used or solved for control problems. Among these noise processes are the family of fractional Brownian motions. While Brownian motion is included in this family, all of the other members are neither semimartingales nor Markov processes. Thus the usual stochastic calculus or the methods from Markov processes cannot be used. However, empirical data in a wide variety of physical phenomena, such as turbulence and telecommunications, provides evidence of the necessity for using these fractional Brownian motions in mathematical models. Thus it is important to consider control systems that are driven by an arbitrary fractional Brownian motion.

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Document Details

Document Type
Technical Report
Publication Date
Feb 11, 2012
Accession Number
ADA567576

Entities

People

  • Bozenna Pasik-duncan
  • T. E. Duncan

Organizations

  • University of Kansas

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Brownian Motion
  • Control Systems
  • Differential Equations
  • Equations
  • Ergodic Processes
  • Hilbert Space
  • Information Theory
  • Linear Systems
  • Markov Processes
  • Mathematical Models
  • Mathematics
  • Models
  • Nonlinear Systems
  • Partial Differential Equations
  • Riccati Equation
  • Stochastic Control
  • Students

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.