FORMULATING THE LEAST-SQUARE REGRESSION FOR CONTINUOUS ANALYSIS.

Abstract

Numerous techniques have been developed to adapt to changes in process parameters, most of which require the system to be taken off control and disturbed so that data may be collected for either on-line or off-line analysis. These techniques in many cases cannot be justified even though adaptive modeling is needed. The requirement that the process be intentionally disturbed in most cases is undesirable and frequently completely impractical. Also, the actual computer programs required to perform the analysis are generally long both in execution time and computer storage. This report demonstrates that in most cases these requirements are not necessary for either on-line or off-line analysis and that the regression problem can be formulated so that changes in model parameters can be continually monitored under normal controlled operation without extensive use of valuable computer time or storage. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1969
Accession Number
AD0688802

Entities

People

  • Cecil L. Smith
  • Charles F. Moore
  • Paul W. Murrill

Organizations

  • Louisiana State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Automata
  • Computer Programs
  • Computers
  • Computing Devices

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Systems Analysis and Design