- 會議論文
Entropy Linearization Method for Response Prediction of Nonlinear Stochastic Dynamic Systems
並列摘要
A new hybrid method for the response analysis of nonlinear stochastic dynamic systems is proposed. First, the stationary probability density functions of the stochastic systems are estimated by maximum entropy approach based on available information about the responses through experiential data, equations of moments, or Monte Carlo simulations. An equivalent linear model which guarantees entropy upper bound in stationary is then constructed by non-Gaussian linearization method according to the obtained maximum-entropy probability density function. As a result, the stationary and non-stationary responses of the nonlinear stochastic dynamic systems can be predicted by this robust-entropy equivalent linear model. The performance and validity of the proposed hybrid method are compared and supported by some oscillators with exact solutions and through conventional Gaussian linearization method.
被引用紀錄
延伸閱讀
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