Analyzing iterations in identification with application to nonparametric <i>H</i>_∞-norm estimation

作     者：Rojas, Cristian R. Oomen, Tom Hjalmarsson, Hakan Wahlberg, Bo 

作者机构：KTH Royal Inst Technol Automat Control Lab S-10044 Stockholm Sweden KTH Royal Inst Technol ACCESS Linnaeus Ctr S-10044 Stockholm Sweden Eindhoven Univ Technol Dept Mech Engn Control Syst Technol Grp NL-5600 MB Eindhoven Netherlands 

出 版 物：《AUTOMATICA》 (自动学)

年 卷 期：2012年第48卷第11期

页      面：2776-2790页

核心收录：

学科分类：0711[理学-系统科学] 0808[工学-电气工程] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 0701[理学-数学] 071101[理学-系统理论] 

基　　金：European Research Council under the advanced grant LEARN Swedish Research Council [621-2009-4017] 

主　　题：Nonparametric methods Iterative modeling and control design Input and excitation design 

摘      要：Many iterative approaches in the field of system identification for control have been developed. Although successful implementations have been reported, a solid analysis with respect to the convergence of these iterations has not been established. The aim of this paper is to present a thorough analysis of a specific iterative algorithm that involves nonparametric H-infinity-norm estimation. The pursued methodology involves a novel frequency domain approach that addresses both additive stochastic disturbances and input normalization. The results of the convergence analysis are twofold: (1) the presence of additive disturbances introduces a bias in the estimation procedure, and (2) the iterative procedure can be interpreted as experiment design for H-infinity-norm estimation, revealing the value of iterations and limits of accuracy in terms of the Fisher information matrix. The results are confirmed by means of a simulation example. (c) 2012 Elsevier Ltd. All rights reserved.