Time-domain nonlinear system identification method based on empirical slow-flow analysis

Young S. Lee, Alexander F Vakakis, D. Michael McFarland, Lawrence Bergman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a physics-based interpretation of slow-flow dynamics derived by empirical mode decomposition (EMD), which possesses equivalence or close correspondence with the analytical slow-flow model (e.g., by means of complexificationaveraging technique). Based on this observation, we develop a nonlinear system identification (NSI) method for direct analysis of measured time series, which is capable of analyzing strongly nonlinear, complex, multi-component systems. Nonlinear modal interactions can be described by means of intrinsic mode oscillators (IMOs), which are typically expressed as a set of linear, damped oscillators with nonhomogeneous terms that carry the nonlinear modal interactions at the different time scales of the dynamics. Both analytical and empirical slow flows are utilized to calculate the nonlinear modal interactions and validated by comparing the IMO solutions and the corresponding intrinsic mode functions obtained from EMD analysis. A main advantage of our proposed technique is that it is nonparametric, eliminating the necessity for a priori assumption of functional forms for stiffness and damping nonlinearities, which might restrict system identification. Hence, it is applicable to a broad range of linear as well as nonlinear dynamical systems, including systems with smooth or non-smooth nonlinearities (such as clearances, vibroimpacts, and dry friction), and strong (even nonlinearizable) or weak nonlinear effects.

Original languageEnglish (US)
Title of host publication51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
StatePublished - Dec 16 2010
Event51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference - Orlando, FL, United States
Duration: Apr 12 2010Apr 15 2010

Publication series

NameCollection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
ISSN (Print)0273-4508

Other

Other51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
CountryUnited States
CityOrlando, FL
Period4/12/104/15/10

Fingerprint

Nonlinear systems
Identification (control systems)
Decomposition
Nonlinear dynamical systems
Control nonlinearities
Time series
Physics
Damping
Stiffness
Friction

ASJC Scopus subject areas

  • Architecture
  • Materials Science(all)
  • Aerospace Engineering
  • Mechanics of Materials
  • Mechanical Engineering

Cite this

Lee, Y. S., Vakakis, A. F., McFarland, D. M., & Bergman, L. (2010). Time-domain nonlinear system identification method based on empirical slow-flow analysis. In 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference [2010-2557] (Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference).

Time-domain nonlinear system identification method based on empirical slow-flow analysis. / Lee, Young S.; Vakakis, Alexander F; McFarland, D. Michael; Bergman, Lawrence.

51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. 2010. 2010-2557 (Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, YS, Vakakis, AF, McFarland, DM & Bergman, L 2010, Time-domain nonlinear system identification method based on empirical slow-flow analysis. in 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference., 2010-2557, Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Orlando, FL, United States, 4/12/10.
Lee YS, Vakakis AF, McFarland DM, Bergman L. Time-domain nonlinear system identification method based on empirical slow-flow analysis. In 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. 2010. 2010-2557. (Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference).
Lee, Young S. ; Vakakis, Alexander F ; McFarland, D. Michael ; Bergman, Lawrence. / Time-domain nonlinear system identification method based on empirical slow-flow analysis. 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. 2010. (Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference).
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