scholarly journals Subspace identification – a Markov parameter approach

2005 ◽  
Vol 78 (17) ◽  
pp. 1412-1436 ◽  
Author(s):  
N. L. C. Chui ◽  
J. M. Maciejowski
Keyword(s):  
Subspace Identification ◽  
Parameter Approach ◽  
Markov Parameter

Application of short-time stochastic subspace identification to estimate bridge frequencies from a traversing vehicle

2021 ◽  
Vol 230 ◽  
pp. 111688
Author(s):  
Nan Jin ◽  
Y.B. Yang ◽  
Elias G. Dimitrakopoulos ◽  
Themelina S. Paraskeva ◽  
Lambros S. Katafygiotis
Keyword(s):  
Subspace Identification ◽  
Stochastic Subspace Identification ◽  
Short Time

scholarly journals Multi-Modal Active Vibration Control of a Lightweight Stress-Ribbon Footbridge Based on Subspace Identification

2017 ◽  
Vol 50 (1) ◽  
pp. 7058-7063
Author(s):  
Xiaohan Liu ◽  
Thomas Schauer ◽  
Arndt Goldack ◽  
Mike Schlaich
Keyword(s):  
Vibration Control ◽  
Active Vibration Control ◽  
Subspace Identification ◽  
Active Vibration

Identification of Linear Tire Cornering Stiffness Using Subspace Methods

2014 ◽  
Vol 701-702 ◽  
pp. 492-497
Author(s):  
Teng Yue Ba ◽  
Xi Qiang Guan ◽  
Jian Wu Zhang
Keyword(s):  
Data Driven ◽  
Subspace Identification ◽  
Subspace Methods ◽  
Identification Methods ◽  
The Road ◽  
Strong Robustness ◽  
Subspace Algorithms ◽  
Double Lane Change ◽  
On The Road ◽  
Lane Change Test

In this paper, subspace identification methods are proposed to estimate the linear tire cornering stiffness, which are only based on the road tests data without any prior knowledge. This kind of data-driven method has strong robustness. In order to validate the feasibility and effectiveness of the algorithms, a series of standard road tests are carried out. Comparing with different subspace algorithms used in road tests, it can be concluded that the front tire cornering stiffness can be estimated accurately by the N4SID and CCA methods when the double lane change test data are taken into analysis.

Subspace Identification of Local Systems in One-Dimensional Homogeneous Networks

2018 ◽  
Vol 63 (4) ◽  
pp. 1126-1131 ◽  
Author(s):  
Chengpu Yu ◽  
Michel Verhaegen ◽  
Anders Hansson
Keyword(s):  
Subspace Identification ◽  
Local Systems ◽  
One Dimensional

scholarly journals Output-Only Identification of System Parameters from Noisy Measurements by Multiwavelet Denoising

2014 ◽  
Vol 6 ◽  
pp. 218328 ◽  
Author(s):  
O. Al-Gahtani ◽  
M. El-Gebeily ◽  
Y. Khulief
Keyword(s):  
Wavelet Transforms ◽  
Model Identification ◽  
Subspace Identification ◽  
Measuring Devices ◽  
Noisy Output ◽  
Output Only ◽  
Modal Values ◽  
Noisy Measurements ◽  
Stochastic Identification ◽  
Wavelet Methods

In this paper we estimate the parameters of a multidimensional system from a record of noisy output measurements by using a multiwavelet denoising technique. In this output-only identification scheme, we extend wavelet denoising methods to the multiwavelet case. After the noise has been removed from the output records by wavelet methods, either full model identification or deterministic subspace identification can be performed. In the former case, full information on the system such as modal values and shapes becomes available by postprocessing. In the latter case, the observable modal values of the system as well as modal shapes at the sensor locations can be extracted from the identified parameters. Additionally, we discuss the requirements on the measuring devices to be compatible with wavelet transforms of a particular type. The validity and merit of the developed scheme are illustrated by examples of numerically simulated and experimentally measured signals, including comparisons with stochastic identification methods.

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