卡尔曼滤波器
估计员
控制理论(社会学)
线性系统
数学
规范(哲学)
有界函数
稳健性(进化)
计算机科学
国家(计算机科学)
数学优化
应用数学
算法
统计
控制(管理)
数学分析
人工智能
基因
生物化学
政治学
法学
化学
作者
Germain García,Sophie Tarbouriech,Pedro L. D. Peres
摘要
Abstract This paper presents a steady‐state robust state estimator for a class of uncertain discrete‐time linear systems with norm‐bounded uncertainty. It is shown that if the system satisfies some particular structural conditions and if the uncertainty has a specific structure, the gain of the robust estimator (which assures a guaranteed cost) can be calculated using a formula only involving the original system matrices. Among the conditions the system has to satisfy, the strongest one relies on a minimum phase argument. It is also shown that under the assumptions considered, the robust estimator is in fact the Kalman filter for the nominal system. Copyright © 2003 John Wiley & Sons, Ltd.
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