Optimality properties in finite sample liidentification with bounded noise
作者:
B. Kacewicz,
M. Milanese,
期刊:
International Journal of Adaptive Control and Signal Processing
(WILEY Available online 1995)
卷期:
Volume 9,
issue 1
页码: 87-96
ISSN:0890-6327
年代: 1995
DOI:10.1002/acs.4480090109
出版商: Wiley Subscription Services, Inc., A Wiley Company
关键词: l1identification;Bounded noise;Almost‐optimal estimates;Almost‐optimal experiments
数据来源: WILEY
摘要:
AbstractIn this paper we investigate finite sample optimality properties for worst‐case l2identification of the impulse response of discrete time, linear, time‐invariant systems. the experimental conditions we consider consist ofmexperiments of lengthN.the measured outputs are corrupted by component‐wise bounded additive disturbances with known bounds. the quantification of the identification error is given by the maximum l1‐norm of the difference between the true impulse response samples and the estimated ones, where the maximum is taken with respect to all admissible plants and all admissible disturbances.First we show that for any given experimental condition, almost‐optimal (within a factor of two) estimates can be obtained by solving suitable linear programmes.Then we study how experimental conditions affect the identification error. Optimality of the experimental data is measured by the diameter of information, a quantity which is at most twice as large as the minimal worst‐case error.We show that the minimum number of experiments allowing us to minimize the diameter of information is m−= 2−N. the values of the diameter of information and the corresponding optimal inputs are derived for the two extreme experimental conditions m
点击下载:
PDF
(520KB)
返 回