Abstract
A new guidance scheme that utilizes a trajectory planning algorithm by energy-to-range ratio has been developed under the circumstance of surplus energy for the terminal area energy management phase of a reusable launch vehicle. The trajectory planning scheme estimates the reference flight profile by piecing together several flight phases that are defined by a set of geometric parameters. Guidance commands are readily available once the best reference trajectory is determined. The trajectory planning algorithm based on energy-to-range ratio is able to quickly generate new reference profiles for testing cases with large variations in initial vehicle condition and energy. The designed flight track has only one turn heading, which simplifies the trajectory planning algorithm. The effectiveness of the trajectory planning algorithm is demonstrated by simulations, which shows that the guided vehicle is able to successfully dissipate energy and reach the desired approach and landing glideslope target with small tracking errors.
Highlights
The descent flight of the reusable launch vehicle (RLV) commonly comprises three mission phases: the reentry phase, the terminal area energy management (TAEM) phase, and the approach and landing phase
A baseline TAEM trajectory is obtained by executing the trajectory planning algorithm with a nominal entry interface state, a nominal ALI state, and nominal RLV aerodynamics
A new guidance scheme based on energy-to-range ratio (E-R) has been developed for the terminal area energy management (TAEM) phase of RLV
Summary
The descent flight of the reusable launch vehicle (RLV) commonly comprises three mission phases: the reentry phase, the terminal area energy management (TAEM) phase, and the approach and landing phase. Horneman and Kluever [5] have presented a TAEM guidance methodology that employs a trajectory planning algorithm that computes a feasible path from the current state to the desired ALI state without relying on a precomputed, stored database of neighboring TAEM trajectories. Kluever et al [6] have proposed an algorithm capable of rapidly generating a feasible TAEM path from the current state to the desired ALI state. Their path-planning algorithm adjusts the TAEM trajectory by iterating on two geometric parameters: Mathematical Problems in Engineering the down-track location of the HAC and its radius.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
