Subspace-Based Identification of a Distributed Nonlinearity in Time and Frequency Domains

被引:1
|
作者
Anastasio, D. [1 ]
Marchesiello, S. [1 ]
Noel, J. P. [2 ]
Kerschen, G. [3 ]
机构
[1] Politecn Torino, Dept Mech & Aerosp Engn, Turin, Italy
[2] Univ Liege, Dept Aerosp & Mech Engn, Space Struct & Syst Lab, Liege, Belgium
[3] Univ Liege, Dept Aerosp, Quartier Polytech, S3L,Mech Engn, Liege, Belgium
来源
关键词
Nonlinear system identification; Subspace identification; Distributed nonlinearity; Geometric nonlinearity; Nonlinear beam;
D O I
10.1007/978-3-319-74280-9_30
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Nonlinear system identification has become of great interest during the last decades. However, a common and shared framework is not present yet, and the identification may be challenging, especially when real engineering structures are considered with strong nonlinearities. Subspace methods have proved to be effective when dealing with local nonlinearities, both in time domain (TNSI method) and in frequency domain (FNSI method). This study reports an improvement for both methods, as a first attempt to account for distributed nonlinearities, which is still an open question in the research community. A numerical beam under moderately large oscillations that exhibits geometric nonlinearity is considered. The object of the identification process is to exploit its behavior through the correct identification of the parameters that define the nonlinearity. Results show a high level of confidence between the two methods, and suggest that a more complete analysis of distributed nonlinear phenomena can be conducted based on these approaches.
引用
收藏
页码:283 / 285
页数:3
相关论文
共 50 条
  • [21] Frequency domain subspace-based identification of discrete-time power spectra from nonuniformly spaced measurements
    Akçay, S
    Türkay, S
    2004 43RD IEEE CONFERENCE ON DECISION AND CONTROL (CDC), VOLS 1-5, 2004, : 851 - 856
  • [22] Comparison of Subspace-based System Identification Techniques
    Kim, Young-Man
    2013 13TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2013), 2013, : 741 - 746
  • [23] Frequency domain subspace-based identification of discrete-time power spectra from uniformly spaced measurements
    Akcay, Huseyin
    AUTOMATICA, 2011, 47 (02) : 363 - 367
  • [24] A subspace-based channel model for frequency selective time variant MIMO channels
    Del Galdo, G
    Haardt, MT
    Milojevic, M
    2004 IEEE 15TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS, VOLS 1-4, PROCEEDINGS, 2004, : 1603 - 1607
  • [25] Subspace-Based Detection and Localization in Distributed MIMO Radars
    Lai, Yangming
    Venturino, Luca
    Grossi, Emanuele
    Yi, Wei
    2022 IEEE 12TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM), 2022, : 365 - 369
  • [26] Subspace-Based Algorithms for Blind ML Frequency and Transition Time Estimation in Frequency Hopping Systems
    Kuo-Ching Fu
    Yung-Fang Chen
    Wireless Personal Communications, 2016, 89 : 303 - 318
  • [27] Subspace-Based Algorithms for Blind ML Frequency and Transition Time Estimation in Frequency Hopping Systems
    Fu, Kuo-Ching
    Chen, Yung-Fang
    WIRELESS PERSONAL COMMUNICATIONS, 2016, 89 (02) : 303 - 318
  • [28] Frequency domain subspace-based identification of discrete-time singular power spectra from uniformly spaced measurements
    Akcay, Huseyin
    2012 AMERICAN CONTROL CONFERENCE (ACC), 2012, : 2677 - 2682
  • [29] Subspace-based blind channel identification for orthogonal modulation
    Klein, A. G.
    Duhamel, P.
    2006 IEEE 7TH WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, VOLS 1 AND 2, 2006, : 512 - +
  • [30] SUBSPACE-BASED FREQUENCY ESTIMATION UTILIZING PRIOR INFORMATION
    Wirfalt, Petter
    Bouleux, Guillaume
    Jansson, Magnus
    Stoica, Petre
    2011 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP), 2011, : 533 - 536