Quadrotor aircraft attitude estimation and control based on Kalman filter

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.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.the National Basic Research Program of China; the National Natural Science Foundation of ChinaEI中文核心期刊要目总览(PKU)中国科技核心期刊(ISTIC)中国科学引文数据库(CSCD)091109-11153