Process Identification Utilizing a Sequential Instrumental Variable Regression Algorithm.

Abstract

Instrumental variable (IV) regression is applied to the estimation of the parameters of a difference equation model of a process subject to noise. The technique preserves the simplicity of least-squares estimation, and is shown to significantly reduce the bias on the parameter estimates caused by measurement noise. A second-order example is used to illustrate the performance of the IV estimator, and to study the selection of sample time and initialization parameters. Demonstration is given on the parameter tracking capability of the dynamic form of the algorithm. The dynamic algorithm is important for use in adaptive control. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1976
Accession Number
ADA032847

Entities

People

  • A. B. Corripio
  • A. T. Touchstone

Organizations

  • Louisiana State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Control Systems
  • Control Systems Engineering
  • Data Science
  • Difference Equations
  • Equations
  • Estimators
  • Filters
  • Identification
  • Information Science
  • Mathematical Filters
  • Measurement
  • Optimal Estimators
  • Regression Analysis
  • Statistical Algorithms
  • Statistical Estimation

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Computational Modeling and Simulation