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Polynomial chaos expansion with fuzzy and random uncertainties in dynamical systems

机译:多项式混沌扩展在动力系统中具有模糊和随机的不确定性

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This paper proposes a surrogate model which is able to deal with mixed uncertain dynamical systems: some uncertain parameters are modelled by random variables whereas others are represented by fuzzy variables. Polynomial chaos expansions (PCE) were developed for uncertainty propagation through random systems. However, fuzzy variables may also be described with polynomial chaos: in particular, Legendre polynomials are well adapted to fuzzy variables. Hence we propose a polynomial chaos expansion, which is able to describe an uncertain dynamical system with both random and fuzzy variables. The method is applied to simulate an uncertain bar and the results are compared to MCS results. Thus the PCE is successfully applied to dynamical systems with both fuzzy and random uncertainties. This study also highlights the issue of the description of the outputs: which quantities should be calculated to represent the behaviour of the uncertain outputs? In the case studies, the fuzzy mean and the fuzzy standard deviation are used to describe the output properties.
机译:本文提出了一种能够处理混合不确定动态系统的代理模型:一些不确定的参数由随机变量建模,而其他参数是由模糊变量表示的。多项式混沌扩展(PCCE)是通过随机系统进行不确定性传播的。然而,模糊变量也可以用多项式混沌描述:特别地,Legendre多项式很好地适应模糊变量。因此,我们提出了一种多项式混沌扩展,其能够描述具有随机和模糊变量的不确定动态系统。该方法应用于模拟不确定的栏,并将结果与​​MCS结果进行比较。因此,PCE成功地应用于具有模糊和随机的不确定性的动态系统。本研究还突出了输出描述的问题:应该计算哪些数量以表示不确定输出的行为?在案例研究中,模糊均值和模糊标准偏差用于描述输出特性。

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