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Maneuver load alleviation for high performance aircraft robust to flight condition variations

机译:用于高性能飞机的机动负荷减轻飞行条件变化的强大

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The design of a robust maneuver load alleviation (MLA) system for a high-performance aircraft is studied in this paper. First, the aeroservoelastic (ASE) models of a high-performance military aircraft in climbing maneuver at varying Mach numbers are established. Then, a linear parameter-varying (LPV) model of the ASE systems is constructed and an H infinity robust controller is designed based on the LPV model. The robust control is realized via a pair of outboard ailerons to alleviate the wing-root bending moments in the climbing maneuvers. To compensate the loss of performance in the load alleviation, a controller based on recurrent neural networks is designed in the flight control. Finally, some numerical simulations are made to testify the performance and robustness of the MLA system.
机译:本文研究了用于高性能飞机的强大机动负荷缓解(MLA)系统的设计。 首先,建立了高性能军用飞机的Aeroservoelastic(ASE)模型在不同马赫数的攀登机动中。 然后,构造ASE系统的线性参数变化(LPV)模型,并且基于LPV模型设计了H无限鲁棒控制器。 通过一对舷外亚能器实现了鲁棒控制,以减轻攀爬式演习中的机翼根弯矩。 为了补偿载荷减轻的性能损失,基于经常性神经网络的控制器设计在飞行控制中。 最后,进行了一些数值模拟,以证明MLA系统的性能和鲁棒性。

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