SUBOPTIMAL ALGORITHMS FOR WORST-CASE IDENTIFICATION IN H-INFINITY AND MODEL VALIDATION

被引：4
|
作者：
GU, GX
机构：
[1] Department of Electrical and Computer Engineering, Louisiana State Universit, Baton Rouge, LA
来源：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1994年 / 39卷 / 08期
基金：
美国国家科学基金会;
关键词：
D O I：
10.1109/9.310044
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
New algorithms based on convex programming are proposed for worst case system identification. The algorithms are optimal within a factor of two asymptotically. Further, model validation, or data consistency, is embedded in the identification process. Explicit worst case identification error bounds in the H(infinity) norm are also derived for both uniformly and nonuniformly spaced frequency response samples.
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页码：1657 / 1661
页数：5
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