This work would not have been as successful without the superb guidance of Professor Ping Lu. His knowledge and motivational factors contributed greatly to the development of the skip guidance algorithm. Throughout the development process, the discussions held with him were of fundamental importance in resolving key issues. The computational resources provided greatly sped up extensive Monte Carlo simulations. Professor Lu made excellent suggestions in choosing coursework, that provided additional ideas for the development of the algorithm. The author would also like to the program of study committee for their helpful ideas for improving this dissertation. Many thanks to the bevy of graduate students who provided answers to questions, helpful suggestions, help with the L A T E Xwriting, and general camaraderie. These students include
The dramatic increase in computational power since the Apollo program has enabled the development of numerical predictor-corrector (NPC) entry guidance algorithms that allow on-board accurate determination of a vehicle's trajectory. These algorithms are sufficiently mature to be flown. They are highly adaptive, especially in the face of extreme dispersion and off-nominal situations compared with reference-trajectory following algorithms. The performance and reliability of entry guidance are critical to mission success. This paper compares the performance of a recently developed fully numerical predictor-corrector entry guidance (FNPEG) algorithm with that of the Apollo skip entry guidance. Through extensive dispersion testing, it is clearly demonstrated that the Apollo skip entry guidance algorithm would be inadequate in meeting the landing precision requirement for missions with medium (4000-7000 km) and long (>7000 km) downrange capability requirements under moderate dispersions chiefly due to poor modeling of atmospheric drag. In the presence of large dispersions, a significant number of failures occur even for shortrange missions due to the deviation from planned reference trajectories. The FNPEG algorithm, on the other hand, is able to ensure high landing precision in all cases tested. All factors considered, a strong case is made for adopting fully numerical algorithms for future skip entry missions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations鈥揷itations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.