Equivalent Linearization for the Nonstationary Response Analysis of Nonlinear Systems with Random Parameters

Abstract

This paper presents an approach for analyzing nonlinear systems with parameter uncertainty subjected to stochastic excitation. The uncertain parameters are modeled as time-independent random variables. A general solution procedure based on equivalent linearization is presented. The set of orthogonal polynomials associated with the probability density function is used as the solution basis for the response moments. In addition, the instantaneous equivalent stiffness and damping matrices are approximated as quadratic random functions. The resulting Liapunov system with explicit random coefficients can then be converted into a deterministic system using the method of weighted residuals. Applications to single-degree-of-freedom uncertain systems are given and the accuracy of the results is validated.