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Minimum-fuel Optimal Trajectory for Reusable First-stage Rocket Landing Using Particle Swarm Optimization
Kevin Spencer G. Anglim
出版
California State University, Long Beach
, 2016
ISBN
136936816X
9781369368161
URL
http://books.google.com.hk/books?id=zTWeswEACAAJ&hl=&source=gbs_api
註釋
Abstract: Reusable Launch Vehicles (RLVs) present a more environmentally-friendly and cost-effective approach to accessing space when compared to traditional launch vehicles that are discarded after each flight. This paper studies the recyclable nature of RLVs by presenting a solution method for determining minimal-fuel optimal trajectories using principles from optimal control theory and Particle Swarm Optimization (PSO). The problem is formulated as a minimum-fuel, minimum-landing error powered descent problem where it is desired to move the RLV from a fixed set of initial conditions to three different sets of terminal conditions: an unspecified downrange landing, a specified downrange landing, and a return-to-launch-site landing. However, unlike other powered descent studies, this paper considers the highly nonlinear effects caused by atmospheric drag, which are often ignored for similar powered descent studies on the Moon or Mars. Rather than optimize the controls directly, the throttle control is assumed to be bang-off-bang with a predetermined thrust direction for each phase of flight. An overview of optimal control theory and particle swarm optimization is first presented. The PSO method is presented and verified in a one-dimensional comparison study, and is then applied to the two-dimensional cases, the results of which are illustrated.