QUASILINEARIZATION, SYSTEM IDENTIFICATION, AND PREDICTION

Abstract

An adaptive controller is one which has the capability of learning about unknown aspects of a system being controlled and then modifying its control regime in an effort to improve the quality of the control exerted. A mathematical formulation and computational solution of the problems of system identification and the determination of unmeasurable state variables on the basis of observations of a process, two topics of central importance in the design of adaptive controllers are presented. The approach suggested-based on the theory of quasilinearization-is an outgrowth of continuing RAND research on the computational solution of multi-point boundary-value problems. The paper should be of interest to control engineers and numerical analysts.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1963
Accession Number
AD0414525

Entities

People

  • Harriet H. Kagiwada
  • Richard E. Bellman
  • Robert E. Kalaba

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Biological Sciences
  • Boundaries
  • Boundary Value Problems
  • Control Systems Engineering
  • Differential Equations
  • Equations
  • Government Procurement
  • Identification
  • Iterations
  • Linear Algebraic Equations
  • New York
  • Nonlinear Differential Equations
  • Observation
  • Tank Guns
  • United States

Readers

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