STATE ESTIMATION IN DISTRIBUTED PARAMETER SYSTEMS VIA LEAST SQUARES AND INVARIANT EMBEDDING

THE PURPOSE OF THIS PAPER IS TO REPORT THE EXTENSION OF D. M. DETCHMENDY AND R. SRIDHAR'S PIONEERING RESULTS TO OBTAIN A BETTER SOLUTION TO THE OPTIMAL FILTERING ESTIMATE OF A NOISY NONLINEAR PARTIAL DIFFERENTIAL. THEIR ALGORITHMS FOR FILTERING, SMOOTHING, AND PREDICTION ESTIMATES OF LUMPED PARAMETER SYSTEM STATES WERE GENERATED BY THE CLASSICAL LEAST SQUARES ERROR CRITERION COMBINED WITH AN INVARIANT EMBEDDING TECHNIQUE. THESE EQUATIONS CONSTITUTE A BOUNDARY VALUE PROBLEM WHICH IS TRANSFORMED INTO AN INITIAL VALUE PROBLEM THROUGH THE USE OF AN INVARIANT EMBEDDING TECHNIQUE. /UMTA/

  • Supplemental Notes:
    • PROJ NO URT-36
  • Corporate Authors:

    University of Minnesota, Minneapolis

    Department of Electrical Engineering, 200 Union Street, SE
    Minneapolis, MN  United States  55455-0220
  • Authors:
    • Lamont, G B
    • Kumar, K S
  • Publication Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 00228242
  • Record Type: Publication
  • Source Agency: Urban Mass Transportation Administration
  • Files: TRIS, USDOT
  • Created Date: Jan 3 1973 12:00AM