A fast nonlinear model identification method

被引：188

作者：

Li, K ^{[1
]}

Peng, JX ^{[1
]}

Irwin, GW ^{[1
]}

机构：

[1] Queens Univ Belfast, Sch Elect & Elect Engn, Belfast BT9 5AH, Antrim, North Ireland

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2005年 / 50卷 / 08期

基金：

英国工程与自然科学研究理事会;

关键词：

computational complexity; fast recursive algorithm; nonlinear system identification; numerical stability;

D O I：

10.1109/TAC.2005.852557

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem recursively over the model order without requiring matrix decomposition. The computational complexity of both algorithms is analyzed, along with their numerical stability. The new method is shown to require much less computational effort and is also numerically more stable than OLS.

引用

页码：1211 / 1216

页数：6

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