Abstract
Due to the influence of uncertainty in the reentry trajectory of hypersonic aircraft, it is difficult with conventional deterministic trajectory optimization (DTO) methods to ensure that the actual trajectory meets the required guidance accuracy and constraints. In this paper, the uncertainty of aerodynamic parameters for a hypersonic telescopic wing morphing aircraft is considered to establish a robust trajectory optimization (RTO) problem model. To solve this problem, a two-layer optimization strategy combining a multiobjective evolutionary algorithm (MOEA) and generalized polynomial chaos (gPC) is proposed. In the inner layer, non-intrusive gPC is used for uncertainty propagation of random variables. In the outer layer, push and pull search algorithm (PPS) uses the statistical characteristics calculated by the inner layer to globally search for a robust solution set. The simulation results show that the proposed strategy can achieve a multiobjective solution set with better resistance to aerodynamic disturbances compared with DTO results.
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Yang, H., Chao, T., Wang, S. (2023). Robust Multiobjective Trajectory Optimization for Hypersonic Telescopic Wing Morphing Aircraft. In: Fu, W., Gu, M., Niu, Y. (eds) Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022). ICAUS 2022. Lecture Notes in Electrical Engineering, vol 1010. Springer, Singapore. https://doi.org/10.1007/978-981-99-0479-2_232
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DOI: https://doi.org/10.1007/978-981-99-0479-2_232
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Online ISBN: 978-981-99-0479-2
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