In this contribution, we investigate the accuracy of surrogate models for fuzzy systems. Within a virtual tolerance analysis, unknown uncertainties are considered by fuzzy numbers. These fuzzy numbers consist of higher‐dimensional intervals, where each interval is assigned a membership value. To reproduce fuzzy numbers correctly, a large number of system evaluations is needed. Instead of evaluating numerically expensive full systems, we employ surrogate models with radial basis functions. In order to find sufficiently accurate surrogate models with as few as possible sampling points, we investigate the influence of the sampling points on the respective fuzzy number intervals. As an example, we investigate the tilting of an X‐ray aperture, which shows different accuracy for different sampling strategies. The reference results for the nonlinear multi‐body system are calculated by a Matlab optimizer and are compared to the results of the surrogate models. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Proceedings in Applied Mathematics & Mechanics – Wiley
Published: Jan 1, 2017
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