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Response of Systems Under Non-Gaussian Random Excitations

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An Erratum to this article was published on 25 January 2007

Abstract

The approach of nonlinear filter is applied to model non-Gaussian stochastic processes defined in an infinite space, a semi-infinite space or a bounded space with one-peak or multiple peaks in their spectral densities. Exact statistical moments of any order are obtained for responses of linear systems jected to such non-Gaussian excitations. For nonlinear systems, an improved linearization procedure is proposed by using the exact statistical moments obtained for the responses of the equivalent linear systems, thus, avoiding the Gaussian assumption used in the conventional linearization. Numerical examples show that the proposed procedure has much higher accuracy than the conventional linearization in cases of strong system nonlinearity and/or high excitation non-Gaussianity.

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Authors and Affiliations

  1. Center for Applied Stochastics Research, Florida Atlantic University, Boca Raton, FL, 33431, U.S.A.

    G. Q. Cai

  2. Disaster Prevention Research Institute, Kyoto University, Uji, Kyoto, 611-0011, Japan

    Y. Suzuki

Authors
  1. G. Q. Cai
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  2. Y. Suzuki
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Corresponding author

Correspondence to G. Q. Cai.

Additional information

An erratum to this article is available at http://dx.doi.org/10.1007/s11071-006-9159-0.

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Cai, G.Q., Suzuki, Y. Response of Systems Under Non-Gaussian Random Excitations. Nonlinear Dyn 45, 95–108 (2006). https://doi.org/10.1007/s11071-006-1461-3

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  • DOI: https://doi.org/10.1007/s11071-006-1461-3

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