Model Fidelity Studies for Rapid Trajectory Optimization

Hood, Lisa; Bennett, Gerard; Parish, Julie J.

doi:10.2514/6.2019-0430

Cited by 4 publications

(1 citation statement)

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“…Control, guidance, and navigation of hypersonic vehicles is a challenging problem and active research area due to complex nonlinear physics and fast time scales. We demonstrate the utility of our proposed method to control a three degree of freedom point-mass model of a hypersonic glide vehicle using an aerodynamic surrogate model trained on data from the NASA X43 flight tests [12,[14][15][16].…”

Section: X43 Trajectory Controlmentioning

confidence: 99%

Sensitivity driven experimental design to facilitate control of dynamical systems

Hart¹,

Waanders²,

Hood³

et al. 2022

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Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. This article proposes an optimization centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA's X-43 hypersonic flight tests.

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Section: X43 Trajectory Controlmentioning

confidence: 99%