Basic Optimal Estimation and Control Problems in Hilbert Space.

Abstract

The recently developed mathematical framework of Hilbert resolution space valued random processes is used to formulate and solve an abstract quadratic optimization problem. By particularizing the description of the operators appearing in the statement and solution formula of this problem one rediscovers and generalizes most of the classical estimation and control theory problem statements and results. These results include, among others, the Wiener smoothing prediction filter, the Kalman regulator, the Kalman-Bucy filter, the stochastic control separation principle and the more recent Youla-Jabr-Bongiorno optimal servo problem solution. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1978
Accession Number
ADA055614

Entities

People

  • L. J. Tung
  • R. M. Desantis
  • R. Saeks

Organizations

  • Texas Tech University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Control Systems
  • Control Theory
  • Differential Equations
  • Electrical Engineering
  • Engineering
  • Hilbert Space
  • Mathematical Filters
  • Optimization
  • Partial Differential Equations
  • Probability
  • Random Variables
  • Regulators
  • Stochastic Control
  • Stochastic Processes
  • Systems Science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Theoretical Analysis.

Technology Areas

  • Space
  • Space - Spacecraft Maneuvers