REDUCTION AND IDENTIFICATION OF MULTIVARIABLE PROCESSES USING REGRESSION ANALYSIS

被引：3

作者：

GRAUPE, D

SWANICK, BH

CASSIR, GR

机构：

[1] Department of Mechanical Engineering, Technion Israel Institute of Technology, Haifa

[2] Department of Electrical Engineering and Electronics, Liverpool University, Liverpool

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1968年 / AC13卷 / 05期

关键词：

D O I：

10.1109/TAC.1968.1098971

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper is concerned with the application of multivariate regression analysis to the reduction of multivariable control problems and to the identification of linear and nonlinear time-varying processes. Reduction is performed by grouping the input and output variables of a many variable process into a small number of groups. Control is exercised in terms of a few variables, each representing such a group. Regression is further applied to the dynamic identification of reduced or unreduced linear and nonlinear multivariable processes where no a priori information of the dynamic characteristics is available. Both reduction and identification may be performed on-line. The resulting techniques are conveniently incorporated in control procedures based on dynamic programming and on predictive adaptation. Copyright © 1968 by The Institute of Electrical and Electronics Engineers, Inc.

引用

页码：564 / &