This paper presents the design and verification of a nonlinear model inversion (NMI) controller for the maneuver load alleviation of a pitching oscillating wing based on spanwise-distributed active camber morphing. Recurrent neural networks (RNNs) are used to predict nonlinear and unsteady aerodynamic forces due to wing's large amplitude pitching maneuver, and a fully connected neural network is introduced to build the dynamic inversion of the aeroelastic system for control law design. The inversed system is concatenated with a PI controller to assemble a nonlinear active controller. The controller is first utilized in an offline environment for a 1DoF pitching finite-span wing with spanwise-distributed active camber morphing and then verified in CFD-based fluid-structure-control coupling simulation. The results show that the offline controller could eliminate the maneuver load. In the online CFD-based fluid-structure-control simulation, the bending moment can be alleviated by 38%.

中文翻译：

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通过翼展分布的外倾角变形减轻俯仰翼的主动机动载荷


本文提出了一种非线性模型反演 （NMI） 控制器的设计和验证，用于基于翼展分布主动外倾角变形的俯仰摆动翼的机动载荷减轻。采用递归神经网络 （RNN） 预测机翼大振幅俯仰机动引起的非线性和非定常空气动力，并引入全连接神经网络构建气动弹性系统的动态反演，用于控制律设计。反转系统与 PI 控制器连接以组装非线性有源控制器。该控制器首先在离线环境中用于具有翼展分布主动外倾角变形的 1DoF 俯仰有限跨度机翼，然后在基于 CFD 的流固耦合仿真中得到验证。结果表明，离线控制器可以消除机动载荷。在基于 CFD 的在线流固耦合控制仿真中，弯矩可以减少 38%。