.png){kind=icon}
返回
Algorithms for deterministic balanced subspace identification
.png){kind=icon}
OA
AI
DOI：10.1016/j.automatica.2004.10.007.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
New algorithms for identification of a balanced state space representation are proposed. They are based on a procedure for the estimation of impulse response and sequential zero input responses directly from data. The proposed algorithms are more efficient than the existing alternatives that compute the whole Hankel matrix of Markov parameters. It is shown that the computations can be performed on Hankel matrices of the input-output data of various dimensions. By choosing wider matrices, we need persistency of excitation of smaller order. Moreover, this leads to computational savings and improved statistical accuracy when the data is noisy. Using a finite amount of input-output data, the existing algorithms compute finite time balanced representation and the identified models have a lower bound on the distance to an exact balanced representation. The proposed algorithm can approximate arbitrarily closely an exact balanced representation. Moreover, the finite time balancing parameter can be selected automatically by monitoring the decay of the impulse response. We show what is the optimal in terms of minimal identifiability condition partition of the data into past and future. (c) 2004 Elsevier Ltd. All rights reserved.
Keyword:
exact deterministic subspace identification
balanced model reduction
approximate system identification
MPUM
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.9
论文数:
1.2W
被引数:
5.2W
机构
暂无机构信息
引用论文
分享收藏Field performance of conifer and hardwood species 5 years after nursery inoculation in the Canadian Prairie Provinces.png)
New Forests
New ForestsIF0
PREAI
分享收藏Intermetallic Alloys Ni<sub>3</sub>Si and Ni<sub>3</sub>(Si,Ti): Microstructures and Properties
PREAI
分享收藏 没有更多内容
没有更多内容