Constrained parameter estimation with applications to blending operations

被引：17

作者：

Murakami, K ^{[1
]}

Seborg, DE ^{[1
]}

机构：

[1] Univ Calif Santa Barbara, Dept Chem Engn, Santa Barbara, CA 93106 USA

来源：

JOURNAL OF PROCESS CONTROL | 2000年 / 10卷 / 2-3期

关键词：

blending systems; least squares; constrained parameter estimation; inequality constraints; quadratic programming;

D O I：

10.1016/S0959-1524(99)00032-3

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 classical least squares approach to parameter estimation for dynamic models ignores a priori information about the feasible values of the estimated parameters. But in many practical problems, such information is available in the form of upper and lower limits. In this paper, two alternative techniques are evaluated for this important class of constrained parameter estimation problems for dynamic systems. Simulation results for two blending problems illustrate that more accurate parameter estimates and better predictions can be obtained by using a quadratic programming approach. (C) 2000 IFAC. Published by Elsevier Science Ltd. All rights reserved.

引用

页码：195 / 202

页数：8

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