Optical Model Reduction and Robust Feedback Control for Aerodynamics

Abstract

In this project, methods of model reduction that integrate feedback active flow control with applications to nonlinear convection and turbulent flows governed by Navier-Stokes equations are developed. A new methodology which extracts boundary conditions in reduced order proper orthogonal decomposition (POD) and finite difference models is developed. A new model reduction method based on empirical data and balanced truncation was developed and applied to nonlinear Galerkin models. Based on this method a new empirical Hankel norm model reduction algorithm is proposed. These methods are applied to a prototype nonlinear convective problem governed by the two-dimensional (2D) Burgers' equation. The reduced models are used in the design of robust boundary controllers that achieve tracking, and implemented on the full order Computational Fluid Dynamics (CFD) models.

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Document Details

Document Type
Technical Report
Publication Date
Mar 29, 2010
Accession Number
ADA547079

Entities

People

  • Seddik M. Djouadi

Organizations

  • University of Tennessee system

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Chemical Reactions
  • Computational Fluid Dynamics
  • Computational Science
  • Convection
  • Differential Equations
  • Equations
  • Fluid Dynamics
  • Fluid Flow
  • Fluid Mechanics
  • Geometry
  • Information Processing
  • Mathematical Filters
  • Navier Stokes Equations
  • Partial Differential Equations
  • Turbulent Flow
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Calculus or Mathematical Analysis
  • Computational Fluid Dynamics (CFD)