TY - GEN
T1 - Onboard longitudinal trajectory planning for terminal area energy management of reusable launch vehicles
AU - Liang, Zixuan
AU - Li, Qingdong
AU - Ren, Zhang
AU - Shao, Xingyue
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/1/12
Y1 - 2015/1/12
N2 - An onboard trajectory planning algorithm is presented in this paper for the terminal area energy management (TAEM) phase of a reusable launch vehicle (RLV). To satisfy the multiple constraints in the TAEM phase, a profile in the flight-path angle vs. range-to-go space is planned. The optimization of this flight-path angle profile is described as a one-parameter search problem and solved by the Newton iteration method. With the optimized flight-path angle profile, a satisfied longitudinal flight trajectory is generated based on the flight dynamics. Testing for the trajectory planning algorithm is performed in missions with different terminal flight-path angle constraints. The onboard algorithm is indicated effective to generate a constrained longitudinal flight trajectory in 0.5 seconds on a PC. The Monte Carlo simulations are employed in dispersed cases, and the planning algorithm is shown robust in trajectory generation with large initial condition errors of the TAEM phase.
AB - An onboard trajectory planning algorithm is presented in this paper for the terminal area energy management (TAEM) phase of a reusable launch vehicle (RLV). To satisfy the multiple constraints in the TAEM phase, a profile in the flight-path angle vs. range-to-go space is planned. The optimization of this flight-path angle profile is described as a one-parameter search problem and solved by the Newton iteration method. With the optimized flight-path angle profile, a satisfied longitudinal flight trajectory is generated based on the flight dynamics. Testing for the trajectory planning algorithm is performed in missions with different terminal flight-path angle constraints. The onboard algorithm is indicated effective to generate a constrained longitudinal flight trajectory in 0.5 seconds on a PC. The Monte Carlo simulations are employed in dispersed cases, and the planning algorithm is shown robust in trajectory generation with large initial condition errors of the TAEM phase.
UR - http://www.scopus.com/inward/record.url?scp=84922489512&partnerID=8YFLogxK
U2 - 10.1109/CGNCC.2014.7007320
DO - 10.1109/CGNCC.2014.7007320
M3 - Conference contribution
AN - SCOPUS:84922489512
T3 - 2014 IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
SP - 850
EP - 854
BT - 2014 IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
Y2 - 8 August 2014 through 10 August 2014
ER -