Approximation Theory and Computational Methods for the Identification and Control of Distributed Parameter Systems

Abstract

A brief overview and summary of the research carried out in the area of approximation theory and computational methods for the identification and control of distributed parameter systems is provided. In particular, this final report details our efforts during the period 1 November 1990-31 October, 1993 on projects involving the adaptive control and estimation, ana on-line identification of distributed parameter systems (including a collaborative experimental-effort with Air Force personnel at Phillips Laboratory at Edwards Air Force Base), the identification and control of degenerate distributed parameter systems, Multi-grid methods for the solution of optimal LQR control problems for infinite dimensional systems, wavelet based approximation in the optimal LQ control of distributed parameter systems, the identification of nonlinear Volterra equations with application to materials with memory, the LQ control of linear and nonlinear distributed parameter systems with infinite spatial domain, and optimal control and estimation of thermoelastic systems with applications to thermo-acoustic refrigeration. Approximation control, Identification distributed parameter systems.

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Document Details

Document Type
Technical Report
Publication Date
Dec 16, 1993
Accession Number
ADA277335

Entities

People

  • I. G. Rosen

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Air Force Personnel
  • Computational Fluid Dynamics
  • Computational Science
  • Differential Equations
  • Equations
  • Formulas (Mathematics)
  • Functional Analysis
  • Integral Equations
  • Inverse Problems
  • Mathematical Analysis
  • Mathematics
  • Numerical Analysis
  • Partial Differential Equations
  • Students
  • Volterra Equations

Fields of Study

  • Engineering

Readers

  • Calculus or Mathematical Analysis
  • Control Systems Engineering.