Onboard Trajectory Generation for Entry Vehicles via Adaptive Multivariate Pseudospectral Interpolation

摘要: One of the most powerful analysis tools to deal with entry-guidance problems is possibility formulate them as optimal control problems. Environmental constraints, actuator limits, and strict requirements on final conditions can be efficiently transcribed, resulting in a discrete, finite-dimension nonlinear programming (NLP) problem. However, NLP require computational power, which often exceeds vehicle’s onboard capabilities. Moreover, it important ensure that solution adapted actual flight conditions, differ from nominal scenario. This paper proposes an approach based efficient use multivariate pseudospectral interpolation scheme generate real-time capable entry guidance solutions. The proposed trajectory generation algorithm able wide dispersions at interface, improve lateral performance cases where classic bank-reversal logic not sufficient. applied subspaces database pre-computed trajectories, stored onboard. method here for initial-conditions variations, but every mission parameter, allows find corresponding solution. Results have been generated SHEFEX-3, demonstrator vehicle, was planned by German Aerospace Center. Monte-Carlo simulations show how this applicable, yields significant improvements both longitudinal performance, improvement dispersion area about 96%.