A FREQUENCY DOMAIN METHOD FOR ESTIMATING THE PARAMETERS OF A NON-LINEAR STRUCTURAL DYNAMIC MODEL THROUGH FEEDBACK |
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| Affiliation: | 1. LuK GmbH & Co. KG, Department Calculation, Industriestraße 3, 77815 Bühl, Germany;2. Department of Engineering Mechanics (ITM), Karlsruhe Institute of Technology (KIT), Kaiserstraße 10, 76131 Karlsruhe, Germany;1. Department of Mechanical Science and Engineering, University of Illinois, Urbana, IL 61801, United States;2. Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States;3. Department of Mechanical Engineering, University of Wisconsin at Madison, Madison, WI 53706, United States;4. Department of Aerospace Engineering, University of Illinois, Urbana, IL 61801, United States;1. Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom;2. Department of Mechanical Engineering, University of Bristol, Bristol, United Kingdom;1. Department of Mechanical Science and Engineering, University of Illinois, Urbana, IL 61801, USA;2. Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA;3. Department of Mechanical Engineering, University of Wisconsin, Madison, WI 53706, USA;4. Department of Aerospace Engineering, University of Illinois, Urbana, IL 61801, USA |
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| Abstract: | A unifying perspective of non-linear structural dynamic systems as linear in the open loop with non-linear feedback in the closed loop has recently been revisited by the authors. The authors have previously used feedback to derive a new formulation of frequency response function matrices of non-linear systems, which are described as modulations of nominal linear systems. The modulation creates a pseudo-separation of the linear and non-linear dynamics of the system. The present article derives a new method for estimating parameters of non-linear parametric models that uses internal feedback to account for non-linearities. The main advantage of the new formulation of non-linear system identification is its simplicity. Moreover, the method estimates the linear frequency response matrix and non-linear system parameters at forced and unforced degrees of freedom of general multiple-degree-of-freedom non-linear systems simultaneously. This article demonstrates the implementation of this method on simulated data from single- and multiple-degree-of-freedom lumped parameter models. |
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