ISSUES IN NONLINEAR STOCHASTIC GREY BOX IDENTIFICATION

被引：53

作者：

BOHLIN, T ^{[1
]}

GRAEBE, SF ^{[1
]}

机构：

[1] UNIV NEWCASTLE,CTR IND CONTROL SCI,CALLAGHAN,NSW 2308,AUSTRALIA

来源：

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING | 1995年 / 9卷 / 06期

关键词：

CAD; GREY BOX IDENTIFICATION; MODELING; MULTIVARIABLE SYSTEMS; NONLINEAR SYSTEMS; PARAMETER ESTIMATION; SOFTWARE TOOLS; STOCHASTIC SYSTEMS; SYSTEM IDENTIFICATION;

D O I：

10.1002/acs.4480090603

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Grey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This, contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.

引用

页码：465 / 490

页数：26