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DOB-Based Neural Control of Flexible Hypersonic Flight Vehicle Considering Wind Effects

机译:考虑风效应的基于DOB的柔性超音速飞行器神经控制

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This paper investigates the disturbance observer (DOB)-based neural adaptive control on the longitudinal dynamics of a flexible hypersonic flight vehicle (HFV) in the presence of wind effects. The coupling effect between flexible states and rigid body, and the accessional angle of attack (AOA) due to wind, is modeled as unknown disturbance, where the nonlinear DOB is constructed using the neural approximation. For the weight update in neural networks (NNs), a novel algorithm is proposed with the additional prediction error derived from the serial–parallel estimation model (SPEM) using both neural approximation and disturbance estimation. Different from previous work, the wind effect is taken into the hypersonic flight dynamics for realistic analysis, and the novel controller is designed using compound estimation, where the NN and the DOB are constructed to deal with aerodynamic uncertainty and unknown disturbance. Simulation studies of a flexible HFV with wind effects show that the proposed controller can achieve high tracking accuracy, while the compound estimation can closely follow the system uncertainty with fast convergence.
机译:本文研究了基于扰动观测器(DOB)的神经自适应控制,该控制对存在风效应的柔性高超音速飞行器(HFV)的纵向动力学特性。柔性状态与刚体之间的耦合效应以及风引起的附加迎角(AOA)被建模为未知扰动,其中非线性DOB是使用神经近似构造的。对于神经网络(NNs)中的权重更新,提出了一种新算法,其中使用神经近似和干扰估计从串行-并行估计模型(SPEM)导出了额外的预测误差。与以前的工作不同,将风效应纳入高超音速飞行动力学以进行现实分析,并使用复合估计设计了新颖的控制器,其中构造了NN和DOB以应对空气动力学不确定性和未知扰动。对具有风效应的柔性HFV的仿真研究表明,该控制器可以实现较高的跟踪精度,而复合估计可以快速收敛并紧跟系统不确定性。

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