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Optimal 3-dimension trajectory-tracking guidance for reusable launch vehicle based on back-stepping adaptive dynamic programming

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Abstract

An optimal 3-dimension trajectory-tracking guidance method for Reusable Launch Vehicle (RLV) is proposed based on back-stepping Adaptive Dynamic Programming (ADP). The reference trajectory is generated based on the Gaussian pseudo-spectral method with sufficient saturation constraints on inputs. The reentry dynamics are normalized and modeled as position and velocity subsystems, based on which back-stepping approach is applied to derive the velocity virtual command which effectively reduces the position errors. A single-critic ADP structure is designed to achieve the optimal feedback control with an innovative weight iteration algorithm which reduces training computation, accelerates weights convergence and improves guidance accuracy. The proposed RLV guidance method is validated through the Monte Carlo simulations with initial errors, aerodynamic uncertainty and external disturbances. Comparable results with conventional guidance method based on Linear Quadratic Regulator (LQR) and weight iteration algorithm based on gradient decent demonstrate the advantages of the proposed guidance method.

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Data availability

The datasets generated during the current study are not publicly available due to the fund requirements but are available from the corresponding author on reasonable request.

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Acknowledgements

The research is funded by Aeronautical Science Fund (2019ZC051009).

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  1. School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing, 100191, China

    Xueyun Wang, Zhiyuan Quan & Jingjuan Zhang

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  1. Xueyun Wang
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Correspondence to Jingjuan Zhang.

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Wang, X., Quan, Z. & Zhang, J. Optimal 3-dimension trajectory-tracking guidance for reusable launch vehicle based on back-stepping adaptive dynamic programming. Neural Comput & Applic 35, 5319–5334 (2023). https://doi.org/10.1007/s00521-022-07972-1

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