A novel linear uncertainty propagation method for nonlinear dynamics with interval process
نویسندگان
چکیده
Interval process is a preferable model for time-varying uncertainty propagation of dynamic systems when only the range uncertainties can be obtained. However, nonlinear systems, except Monte Carlo (MC) simulation, there are still few efficient methods under interval model. This paper develops non-intrusive and semi-analytical method, named “convex linearization method (CMLM),” by constructing formulation system in non-probabilistic sense. First, criterion to evaluate difference between original derived, represented discrepancy middle point, radius correlations response. By minimizing these three parameters, coefficients linear equations will optimized obtain system. Then, analytical built calculate response process, without time-consuming analysis To further improve efficiency Chebyshev polynomial introduced approximate analysis. Two numerical examples duffing oscillators vehicle rides set test proposed CMLM. Compared MC with comparable precision, CMLM just needs 1–10% times analyses Furthermore, practical launch ascent trajectory problem black-box dynamics solved by, respectively, method. The results verify capacity deal problems show that performs better terms accuracy, robustness.
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ژورنال
عنوان ژورنال: Nonlinear Dynamics
سال: 2022
ISSN: ['1573-269X', '0924-090X']
DOI: https://doi.org/10.1007/s11071-022-08084-0