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- W3100013015 abstract "A probabilistic performance-oriented control design optimization approach is introduced for flight systems. Aiming at estimating rare-event probabilities accurately and efficiently, subset simulation is combined with surrogate modeling techniques to improve efficiency. At each level of subset simulation, the samples that are close to the failure domain are employed to construct a surrogate model. The existing surrogate is then refined progressively. In return, seed and sample candidates are screened by the updated surrogate, thus saving a large number of calls to the true model and reducing the computational expense. Afterwards, control parameters are optimized under rare-event chance constraints to directly guarantee system performance. Simulations are conducted on an aircraft longitudinal model subject to parametric uncertainties to demonstrate the efficiency and accuracy of this method." @default.
- W3100013015 created "2020-11-23" @default.
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- W3100013015 date "2021-01-04" @default.
- W3100013015 modified "2023-10-16" @default.
- W3100013015 title "Rare-Event Chance-Constrained Flight Control Optimization Using Surrogate-Based Subset Simulation" @default.
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- W3100013015 doi "https://doi.org/10.2514/6.2021-1856" @default.
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