Online subspace identification methods for MIMO model

I. W. Jamaludin, N. Wahab, M. Rahmat, S. Sahlan
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引用次数: 1

Abstract

Subspace model identification (SMI) has been a highly interest of research topic in recent years. Subspace methods such as Multivariable Output Error State Space (MOESP) and Numerical algorithms for Subspace State Space System Identification (N4SID) algorithms are well known and often implemented especially for multivariable identification due to the use of robust numerical tools such as the QR decomposition and singular value decomposition (SVD). SMI algorithms are attractive not only because of their numerical stability and simplicity, but also for the state space form that is very suitable in estimating, predicting, filtering and control design. Several simulation studies for MOESP and N4SID algorithms performed in online version are presented. This paper focuses on computation time, order selection and the stability from both methods when performed online.
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MIMO模型的在线子空间识别方法
子空间模型识别(SMI)是近年来备受关注的研究课题。子空间方法,如多变量输出错误状态空间(MOESP)和子空间状态空间系统识别(N4SID)算法的数值算法是众所周知的,并且由于使用诸如QR分解和奇异值分解(SVD)等鲁棒数值工具,通常用于多变量识别。SMI算法不仅具有数值稳定性和简单性,而且其状态空间形式非常适合于估计、预测、滤波和控制设计。对MOESP和N4SID算法进行了在线仿真研究。本文着重讨论了两种方法在线执行时的计算时间、顺序选择和稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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