Subspace identification of Hammerstein systems using least squares support vector machines

被引：141

作者：

Goethals, I ^{[1
]}

Pelckmans, K ^{[1
]}

Suykens, JAK ^{[1
]}

De Moor, B ^{[1
]}

机构：

[1] Katholieke Univ Leuven, ESAT, SCD, Dept Elect Engn, B-3001 Heverlee, Belgium

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2005年 / 50卷 / 10期

关键词：

Hammerstein models; least squares support; vector machines; subspace identification;

D O I：

10.1109/TAC.2005.856647

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a method for the identification of multiple-input-multiple-output (MIMO) Hammerstein systems for the goal of prediction. The method extends the numerical algorithms for subspace state space system identification (N4SID), mainly by rewriting the oblique projection in the N4SID algorithm as a set of componentwise least squares support vector machines (LS-SVMs) regression problems. The linear model and static nonlinearities follow from a low-rank approximation of a matrix obtained from this regression problem.

引用

页码：1509 / 1519

页数：11

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