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Fusion Attitude Solving Algorithm of Four-Rotor UAV Based on Improved Extended Kalman Filter

机译:基于改进扩展卡尔曼滤波器的四旋翼无人机融合姿态求解算法

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The stability problem of the four-rotor aircraft in flight control is popular in the research of Quadrotors, and the attitude angle is an important flight control parameter for the four-rotor aircraft, which plays a very important role in stable flight. The solution of the attitude angle is actually the fusion of multi-sensor acquisition attitude information. This paper proposes an improved EKF filtering algorithm based on attitude solution. The attitude angle obtained by the complementary filtering is used as the observation variable of the EKF filter equation, The angular velocity of the gyroscope is used as a state variable. Then act on the real-time pose update calculation, thereby outputting the attitude angle information. And based on STM32 MCU to build a four-rotor aircraft experimental platform for performance verification. The results show that the designed algorithm is faster and more acurrate than the convergence rate, which can meet the requirements of precision and real-time performance of the quadrotor.
机译:四旋翼飞行器在飞行控制中的稳定性问题在四旋翼飞行器的研究中很普遍,姿态角是四旋翼飞行器的重要飞行控制参数,在稳定飞行中起着非常重要的作用。姿态角的解决方案实际上是多传感器采集姿态信息的融合。提出了一种改进的基于姿态解的EKF滤波算法。通过互补滤波获得的姿态角用作EKF滤波器方程的观测变量,将陀螺仪的角速度用作状态变量。然后进行实时姿态更新计算,从而输出姿态角信息。并基于STM32 MCU构建了四旋翼飞机性能验证实验平台。结果表明,所设计的算法比收敛速度更快,计算更准确,可以满足四旋翼飞行器精度和实时性的要求。

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