Discrete Model Identification Based on Correlation Functions.
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 system's sampled experimental input-output record. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1971
- Accession Number
- AD0718995
Entities
People
- Armando Corripio
- Brian Froisy
- Cecil Smith
Organizations
- Louisiana State University