摘要
针对两轮自平衡车运行过程中,车身姿态检测时,角速度信号存在随机漂移,角度信号存在动态误差且极易受外界噪声干扰的问题,应用卡尔曼滤波对其倾角与倾角速度进行信号的融合,通过时域上包含噪声的有限测量数据来获取系统的最优状态估计,对倾角信号进行有效的补偿并修正,以减小自平衡车姿态测量误差,提高运算精度。并采用陀螺仪检测角速度信号,加速度计检测角度信号,以MK60嵌入式系统为控制核心,实现了信号的融合,获得了较为理想的车身姿态检测信号。
In the process of two-wheel self-balanced car running,when detecting the body attitude,the angularvelocity signal exists random drift error,the angle signal has the dynamic error and easily interfered by external noise.Therefore,using the Kalman filtering to fuse the angle and angular velocity. Kalman filtering obtains the optimal stateestimation of system by limited measurement data that contains noise in time domain,and to effectively compensateand correct angle signal. So as to reduce the attitude measuring error of two-wheel self-balanced car and improve theaccuracy of operation. Using the gyroscope to detect angular velocity signal,the accelerometer to detect angle signal,with the MK60 embedded system as the control core,it realizes the signal fusion,gets to the ideal body posturedetection signal.
出处
《电气传动》
北大核心
2015年第2期54-57,共4页
Electric Drive
关键词
两轮自平衡车
角度
角速度
卡尔曼滤波
two wheel self-balanced car
angle
angular velocity
Kalman filtering
