单同轴无人机带2自由度推力矢量机构的动态建模与LQR控制

中文摘要 AI 辅助

同轴旋翼无人机因能源效率高和体积小而引起了广泛兴趣，但其在滚转和俯仰控制上存在固有的欠驱动问题，尽管诸如斜盘之类的系统已通过增加机械复杂性为代价规避了这一限制。本研究提出了一种新颖的同轴无人机，辅以二自由度摆锤机构实现主动推力矢量，提供了一种机械上不那么复杂的替代方案。我们开发了一个全面的拉格朗日动力学模型，该模型不忽略所有部件的惯性贡献，包括机体、舵机臂和电机组件。基于悬停平衡点附近的线性化动力学，设计了一个线性二次型调节器（LQR）。考虑执行器动力学和传感器噪声的高保真仿真验证了所提出的架构。扩展卡尔曼滤波器（EKF）将GPS、气压计和IMU的估计值以高精度融合用于状态估计。研究结果验证了该方法在节能、快速同轴无人机上的潜力和可靠性。

英文摘要

Coaxial rotor drones have generated considerable interest because of energy efficiency and small size, but they are afflicted with inherent underactuation for roll and pitch control, although systems like swashplates have circumvented this limitation at the cost of greater mechanical complexity. This work presents a novel coaxial drone supplemented by a two-degreesof-freedom pendulum mechanism for active thrust vectoring that offers a less mechanically complicated alternative. We develop a comprehensive Lagrangian dynamic model that does not ignore the inertial contributions of all the components, including body, servo arms, and motor assembly. A Linear Quadratic Regulator(LQR) is designed based on the linearized dynamics around the hover equilibrium. High-fidelity simulations taking actuator dynamics and sensor noise into account validate the proposed architecture. An Extended Kalman Filter (EKF) blends GPS, barometer, and IMU estimates with high accuracy for state estimation. The findings verify the potential and reliability of this approach for power-saving, rapid coaxial UAVs.

发表机构

• Sharif University of Technology（谢里夫理工大学）

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