An online predictive reentry guidance law for reusable launch vehicles

Abstract

Space applications have raised the demand on autonomy, security and reliability for current reusable launch vehicle (RLV), which require guidance technology of vehicle must have strong robustness and adaptability. Based on preliminary research results, this paper outlines a method of developing an online predictive reentry trajectory planning and guidance law which use both angle-of-attack and angle-of-bank variations to control the reentry trajectory. The trajectory planning is done with the landing point prediction, which induce the energy as the integration variable instead of the time in order to solve the time uncertainty of the reentry process. The reentry dynamical model is built firstly According to the RLV mathematical model and the constraint equations. As the trajectory planning is classified as a two-point boundary value problem, Secondly the constrained optimal problem is converted to an unconstrained optimal problem by introducing augmented state vector. Finally, a numerical solution based on the simplex reflection technique (one of the optimized methods) is employed to solve the unconstrained optimal problem, and the entry online guidance law is achieved. Simulations with the vehicle and trajectory data demonstrate good performance of the guidance algorithms. The main novelty of this work is in applying a new online predictive energy-based guidance strategy that has desirable features as a reference trajectory for tracking.