Comparison of Four On-Line Identification Methods for Multivariable Systems,

Abstract

This paper presents the results of a comparison of four methods for on-line identification of discrete time, linear, time invariant, multivariable systems. The methods chosen for comparison are, the extended Kalman filter, instrumental variables method, extended least squares and stochastic approximations. These methods are applied to both a multivariable system as well as a single input single output system. The computational properties of the methods are compared as well as their convergence properties. Various trade offs between the methods are pointed out.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1974
Accession Number
ADA008729

Entities

People

  • Edwin B. Stear
  • Lawrence W. Nelson

Organizations

  • University of California, Santa Barbara

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Convergence
  • Estimators
  • Filters
  • Identification
  • Kalman Filters
  • Mathematical Filters
  • Mathematics
  • Optimal Estimators

Readers

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