文章基本信息

标题：Application of Rank-Constrained Optimisation to Nonlinear System Identification ∗
本地全文：下载
作者：Ramón A. Delgado ; Juan C. Agüero ; Graham C. Goodwin 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：11
页码：814-818
DOI：10.1016/j.ifacol.2015.09.290
语种：English
出版社：Elsevier
摘要：AbstractNonlinear System Identification has a rich history spanning at least 5 decades. A very flexible approach to this problem depends upon the use of Volterra series expansions. Related work includes Hammerstein models, where a static nonlinearity is followed by a linear dynamical system, and Wiener models, where a static nonlinearity is inserted after a linear dynamical model. A problem with these methods is that they inherently depend upon series type expansions and hence it is dificult to know which terms should be included. In this paper we present a possible solution to this problem using recent results on rank-constrained optimization. Simulation results are included to illustrate the eficacy of the proposed strategy.