Accession Number:

AD0718995

Title:

Discrete Model Identification Based on Correlation Functions.

Descriptive Note:

Technical rept.,

Corporate Author:

LOUISIANA STATE UNIV BATON ROUGE DEPT OF CHEMICAL ENGINEERING

Report Date:

1971-01-01

Pagination or Media Count:

25.0

Abstract:

Using most of the techniques currently available, some information concerning the dynamics of a system must be known before any meaningful control strategy can be implemented. This information can be presented in the form of a plant model which may be obtained in a variety of ways, ranging from a model derived from knowledge of the basic physical phenomena involved to some simple empirical model e.g., first-order lag with dead time. In this paper, a technique of obtaining a dynamic plant model for a general system is presented and applied to two specific cases. The identification technique discussed in this paper produces a discrete model, and as such should be useful in a digital control environment. The basic approach of the technique is to apply a straight-forward multiple linear regression to points on the discret auto- and cross-correlation functions calculated from a systems sampled experimental input-output record. Author

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE