The DelftaCopter is a tilt-body tailsitter unmanned air vehicle which combines a large swashplate controlled helicopter rotor with a biplane delta-wing. Previous research has shown that the large moment of inertia of the wing and fuselage significantly interacts with the dynamics of the rotor. While this rigid rotor cylinder dynamics model has allowed initial flight testing, part of the dynamics remains unexplained. In particular, higher frequency dynamics and the forward flight dynamics were not modeled. In this work, the cylinder dynamics model is compared with the tip-path plane model, which includes the steady-state flapping dynamics of the blades. The model is then extended to include the wing and elevon dynamics during forward flight. Flight test data consisting of excitations with a large frequency content are used to identify the model parameters using grey-box modeling. Since the DelftaCopter is unstable, flight tests can only be performed while at least a rate feedback controller is active. To reduce the influence of this active controller on the identification of the dynamics, one axis is identified at a time while white noise is introduced on all other axes. The tip-path plane model is shown to be much more accurate in reproducing the high-frequency attitude dynamics of the DelftaCopter. The significant rotor–wing interaction is shown to differ greatly from what is seen in traditional helicopter models. Finally, an Linear-Quadratic Regulator (LQR) controller based on the tip-path plane model is derived and tested to validate its applicability. Modeling the attitude dynamics of the unstable DelftaCopter from flight test data has been shown to be possible even in the presence of the unavoidable baseline controller.

中文翻译：

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从飞行试验数据对不稳定的 DelftaCopter 垂直起降尾翼无人机悬停和前飞进行建模

DelftaCopter 是一种倾斜体尾翼无人机，它结合了大型斜盘控制直升机旋翼和双翼三角翼。先前的研究表明，机翼和机身的大转动惯量与旋翼的动力学显着相互作用。虽然这种刚性转子圆柱动力学模型允许进行初始飞行测试，但部分动力学仍然无法解释。特别是，没有对更高频率的动力学和前飞动力学进行建模。在这项工作中，气缸动力学模型与叶尖路径平面模型进行了比较，其中包括叶片的稳态扑动动力学。然后将模型扩展为包括向前飞行期间的机翼和升降副翼动力学。由具有大频率内容的激励组成的飞行测试数据用于使用灰盒建模来识别模型参数。由于 DelftaCopter 不稳定，因此只能在至少速率反馈控制器处于活动状态时进行飞行测试。为了减少这种主动控制器对动力学识别的影响，一次识别一个轴，同时在所有其他轴上引入白噪声。表明尖端路径平面模型在再现 DelftaCopter 的高频姿态动力学方面更加准确。显着的旋翼机翼相互作用与传统直升机模型中所看到的有很大不同。最后，导出并测试了基于尖端路径平面模型的线性二次调节器 (LQR) 控制器以验证其适用性。