N4SID and MOESP Subspace Identification Methods

被引：0

作者：

Jamaludin, I. W. ^{[1
]}

Wahab, N. A. ^{[2
]}

Khalid, N. S. ^{[2
]}

Sahlan, S. ^{[2
]}

Ibrahim, Z. ^{[3
]}

Rahmat, M. F. ^{[2
]}

机构：

[1] Univ Tekn Malaysia Melaka, Fac Elect Engn, Mechatron Dept, Durian Tunggal 76100, Melaka, Malaysia

[2] Univ Teknol Malaysia, Fac Elect Engn, Dept Control & Mechatron Engn, Skudai 81310, Malaysia

[3] Univ Malaysia Pahang, Fac Elect & Elect Engn, Pahang 26600, Malaysia

来源：

2013 IEEE 9TH INTERNATIONAL COLLOQUIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS (CSPA) | 2013年

关键词：

subspace identification; singular value decomposition; Hankel matrices; QR decomposition; MOESP; N4SID; MODEL IDENTIFICATION; SYSTEMS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Multivariable Output Error State Space (MOESP) and Numerical algorithms for Subspace State Space System Identification (N4SID) algorithms are two well known subspace identification techniques discussed in this paper. Due to the use of robust numerical tools such as QR decomposition and singular value decomposition (SVD), these identification techniques are often implemented for multivariable systems. Subspace identification algorithms are attractive since the state space form is highly suitable to estimate, predict, filters as well as for control design. In literature, there are several simulation studies for MOESP and N4SID algorithms performed in offline and online mode. In this paper, order selection, validity and the stability for both algorithms for model identification of a glass tube manufacturing process system is considered. The weighting factor alpha, used in online identification is obtained from trial and error and particle swarm optimization (PSO). Utilizing PSO, the value of alpha is determined in the online identification and a more accurate result with lower computation time is obtained.

引用

页码：140 / 145

页数：6

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