Nonintrusive Global Sensitivity Analysis for Linear Systems With Process Noise
Nonintrusive Global Sensitivity Analysis for Linear Systems With Process Noise
复制标题
具有过程噪声的线性系统的非侵入式全局灵敏度分析
DOI:
10.1115/1.4041622
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发表时间:
2019
影响因子:
2
通讯作者:
Singh, Tarunraj
中科院分区:
文献类型:
--
作者:
Nandi, Souransu;Singh, Tarunraj
The focus of this paper is on the global sensitivity analysis (GSA) of linear systems with time-invariant model parameter uncertainties and driven by stochastic inputs. The Sobol' indices of the evolving mean and variance estimates of states are used to assess the impact of the time-invariant uncertain model parameters and the statistics of the stochastic input on the uncertainty of the output. Numerical results on two benchmark problems help illustrate that it is conceivable that parameters, which are not so significant in contributing to the uncertainty of the mean, can be extremely significant in contributing to the uncertainty of the variances. The paper uses a polynomial chaos (PC) approach to synthesize a surrogate probabilistic model of the stochastic system after using Lagrange interpolation polynomials (LIPs) as PC bases. The Sobol' indices are then directly evaluated from the PC coefficients. Although this concept is not new, a novel interpretation of stochastic collocation-based PC and intrusive PC is presented where they are shown to represent identical probabilistic models when the system under consideration is linear. This result now permits treating linear models as black boxes to develop intrusive PC surrogates.
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DOI:
10.1177/0037549703040943
发表时间:
2003-12-01
影响因子:
1.6
作者:
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通讯作者:
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DOI:
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2007
期刊:
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1988
期刊:
American Control Conference
影响因子:
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作者:
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通讯作者:
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影响因子:
2.7
作者:
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通讯作者:
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DOI:
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发表时间:
2012
期刊:
影响因子:
--
作者:
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通讯作者:
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