A Hankel norm for quadrature rules solving random linear dynamical systems

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摘要

In linear time-invariant dynamical systems, random variables are included to quantify uncertainties. The solution can be expanded into a series with predetermined orthogonal basis functions, which depend on the random variables. We define a norm of Hankel-type associated to a truncated series. A quadrature rule or a sampling method yields approximations of the unknown time-dependent coefficient functions in the truncated series. We arrange a Hankel norm for the quadrature technique in this context. Assuming a convergent sequence of quadrature rules, we show that the Hankel norms of the quadrature methods converge to the Hankel norm of the truncated series. Hence a numerical method is obtained to calculate the Hankel norm of the truncated series approximately. Results of numerical computations confirm the convergence property in a test example.

论文关键词:Linear dynamical system,Random variables,Quadrature rule,Polynomial chaos expansion,Hankel norm,Uncertainty quantification

论文评审过程:Received 27 November 2015, Revised 14 October 2016, Available online 9 November 2016, Version of Record 22 December 2016.

论文官网地址:https://doi.org/10.1016/j.cam.2016.10.035