Computational Methods for Design, Estimation and Real-Time Control of PDE Systems with Applications to Mobile Sensor Networks

Abstract

The primary objectives of this work are the construction of a rigorous mathematical framework and the corresponding computational science tools that can be used to address problems of parameter identification, real-time tracking and estimation for spatially dependent systems. This includes determining optimized sensor/actuator locations for complex hybrid spatial systems to enhance tracking, estimation, information and effectiveness while limiting energy consumption. Reduced-order modeling techniques are implemented as an efficient way to compute the functional gains. We illustrate how a small number of strategically placed sensor/actuator is sufficient to stabilize the flow while inappropriate placement of these sensors could destabilize the flow. Additionally we consider information delays present in the sensor/actuator network. The models are complex multi-scale systems of coupled partial and delay differential equations. We show that under suitable conditions, the coupled delay PDE systems are well posed and we use this corresponding abstract formulation to construct efficient numerical methods for control design.

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Document Details

Document Type
Technical Report
Publication Date
Aug 14, 2013
Accession Number
ADA589255

Entities

People

  • Eugene M. Cliff
  • John A. Burns
  • Lizette Zietsman

Organizations

  • Virginia Tech

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Applied Mathematics
  • Boundaries
  • Closed Loop Systems
  • Computational Fluid Dynamics
  • Computational Science
  • Control Systems
  • Convection
  • Differential Equations
  • Equations
  • Estimators
  • Flow
  • Fluid Flow
  • High Performance Computing
  • Mathematics
  • Navier Stokes Equations
  • Partial Differential Equations
  • Standards

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Robotics and Automation.