基于卡尔曼滤波的四旋翼飞行器姿态估计和控制算法研究(英文)

Quadrotor aircraft attitude estimation and control based on Kalman filter

中文关键词  四旋翼飞行器  卡尔曼滤波  姿态估计  自回归(auto-regressive, AR)模型  双增益PD控制器  悬停控制

英文关键词  quadrotor aircraft  Kalman filter  attitude estimation  auto regressive model  double-gain PD controller  hover control

中文摘要

      四旋翼飞行器作为无人机的一种, 由于其简单气动布局和复杂的动力学模型, 在控制领域获得了越来越多的学术关注；本文首先分析了微机电系统惯性测量单元(MEMS IMU)传感器的误差, 给出了基于自回归(autoregressive, AR)噪声模型的卡尔曼滤波算法设计; 然后根据加速度计和陀螺仪长短周期测量的不同特性, 进一步对姿态数据做互补融合, 实验表明此算法可以实现良好的滤波效果; 基于上面的姿态估计, 本文又提出了一种双增益的PD控制算法对飞行器进行姿态控制; 最后将姿态估计算法和控制算法应用到实验平台中, 可以实现四旋翼在支架上的自主悬停等功能.

英文摘要

      The quadrotor, as one type of unmanned aircraft vehicles, has gained increasing interests in the control community, partially due to its simple aerodynamics and complex dynamics. In this work, a quadrotor system has been constructed with commercial off-the-shelf products. The sensors of inertial measurement unit are micro-electro-mechanical system, whose errors can be analyzed in an auto regressive model. A new attitude estimation scheme based on Kalman filter is proposed, which conducts separate data fusion tasks in both short and long cycle. The proposed attitude sensing method has been validated using the experimental system. In addition, a double-gain proportional differential controller has been designed to regulate the attitude dynamics. A satisfactory control performance has been achieved in some test cases.