Abstract
The task of terminal area energy management (TAEM) is to plan a trajectory from the end of the reentry phase (approximately 30km) to the landing window (approximately 3km). To ensure the safety of the reusable launch vehicle (RLV), both path constraints and terminal constraints should be met. This paper proposes a novel real-time trajectory planning algorithm to deal with the TAEM task. Firstly, the longitudinal trajectory profile and the lateral trajectory profile are designed separately to satisfy the path constraints and the terminal constraints. Secondly, the trajectory parameters are modified online by newton iteration according to the terminal error, which makes the algorithm more robust. Thirdly, taking vehicle damage into consideration, the landing window is chosen by RLV’s range capability and the initial parameters of the trajectory are predicted by the neural network so that the algorithm can meet the real-time requirement. Simulations demonstrate the effectiveness of the proposed scheme.
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References
Hanson, J.M.: A plan for advanced guidance and control technology for 2nd generation reusable launch vehicles. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, pp. 4557- 4577 (2002)
Morio, V., Cazaurang, F., Falcoz, A., Vernis, P.: Robust terminal area energy management guidance using flatness approach. IET Control Theory Appl. 4(3), 472–486 (2010)
Lu, P.: Entry guidance: a unified method. J. Guid. Control. Dyn. 37(3), 713–728 (2014)
Burchett, B.T.: Fuzzy logic trajectory design and guidance for terminal area energy management. AIAA Paper 2004-700 (2004)
Kluever, C.A., Horneman, K.R.: Terminal trajectory planning and optimization for an unpowered reusable launch vehicle. In: Guidance, Navigation, and Control Conference and Exhibit, AIAA, San Francisco, California (2005)
Chartres, J., GraBlin, M., Schneider, G.: Optimisation of the terminal flight phase for a future reusable launch vehicle. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, pp. 6060–6072 (2005)
Poustini, M.J., Esmaelzadeh, R., Adami, A.: A new approach to trajectory optimization based on direct transcription and differential flatness. Acta Astronaut. 107, 1–13 (2015)
**e, G., Shangguan, A.Q., Fei, R., Ji, W.J., Ma, W.G., Hei, X.H.: Motion trajectory prediction based on a CNN-LSTM sequential model. Sci. China Inf. Sci. 63(11), 1–21 (2020)
Yu, X., Fu, Y., Zhang, Y.M.: Aircraft fault accommodation with consideration of actuator control authority and gyro availability. IEEE Trans. Control Syst. Technol. 26(4), 1285–1299 (2017). https://doi.org/10.1109/TCST.2017.2707378. In Press
Yu, X., Li, P., Zhang, Y.M.: The design of fixed-time observer and finite-time fault-tolerant control for hypersonic gliding vehicles. IEEE Trans. Ind. Electron. 65(5), 4135–4144 (2018)
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Zhou, J. et al. (2023). A Real-Time Trajectory Planning and Guidance Algorithm for Terminal Area Energy Management. In: Yan, L., Duan, H., Deng, Y. (eds) Advances in Guidance, Navigation and Control. ICGNC 2022. Lecture Notes in Electrical Engineering, vol 845. Springer, Singapore. https://doi.org/10.1007/978-981-19-6613-2_9
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DOI: https://doi.org/10.1007/978-981-19-6613-2_9
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