Robust optimization of control command for aerospace vehicles with aerodynamic uncertainty
To reduce the design burden of Aerospace Vehicles (ASVs) control systems, this paper proposes a multi-constrained robust trajectory optimization method, which provides a good front-end input for the control system. Differ from the conventional aircraft, some control performance of ASVs is not only r...
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Veröffentlicht in: | Chinese journal of aeronautics 2022-12, Vol.35 (12), p.226-241 |
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container_title | Chinese journal of aeronautics |
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creator | CAO, Rui LIU, Yanbin LU, Yuping |
description | To reduce the design burden of Aerospace Vehicles (ASVs) control systems, this paper proposes a multi-constrained robust trajectory optimization method, which provides a good front-end input for the control system. Differ from the conventional aircraft, some control performance of ASVs is not only related to the model parameters, but also affected by the flight status. Therefore, the robust optimization method combines this characteristic of ASVs, sets the control performance as one of the optimization objectives, and considers the influence of parameter uncertainty. In this method, the polynomial chaos expansion algorithm is used to transform the trajectory optimization problem with uncertain parameters into the equivalent deterministic robust trajectory optimization problem. Finally, compared with traditional deterministic trajectory optimization methods to illustrate the effectiveness of proposed control optimization method. |
doi_str_mv | 10.1016/j.cja.2022.01.011 |
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source | ScienceDirect Journals (5 years ago - present); EZB-FREE-00999 freely available EZB journals |
subjects | Aerospace vehicle Multi-objective optimization Polynomial chaos Uncertain systems |
title | Robust optimization of control command for aerospace vehicles with aerodynamic uncertainty |
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