This paper investigates a numerical predictor-corrector methodology for adaptive and accurate entry guidance for vehicles with low lift-to-drag ratios, such as the Orion Crew Exploration Vehicle. The central ingredient in this approach is bank-angle parameterization. The choice of the bank-angle profile representation determines how the guidance problem will be solved, as well as the efficiency, performance, and robustness of the algorithm. Two popular forms of bank-angle parameterization, one in longitudinal mode and the other in three-dimensional mode, are closely examined. Special new robustification features are designed in the bank-angle parameterization that are shown to noticeably increase the overall performance of the algorithm. With the use of the predictor-corrector entry guidance approach, an interesting characteristic of the entry trajectory of a low-lifting vehicle is identified that reveals a definitive trend between the initial bank-angle magnitude and the peak load factor. Based on this observation, a simple and effective predictive load-relief strategy is developed for low-lifting vehicles. Extensive dispersion simulations are conducted to evaluate and verify the design features of the algorithm. The testing shows that the robustified longitudinal mode of the predictor-corrector entry guidance algorithm consistently offers very satisfactory performance even in highly dispersed cases. Such an algorithm holds distinct potential for onboard applications.
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Ping Lu (2008) studied this question.
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