两轮自平衡车姿态检测与平衡控制

Attitude Detection and Balance Control of Two-wheeled Self-balancing Vehicles

针对两轮自平衡车姿态检测及平衡控制的要求,设计了一种基于传感器数据融合的两轮自平衡车控制策略,在惯性导航学的基础上,综合比较了互补滤波和卡尔曼滤波融合算法情况下姿态检测的实时准确性。采用PID控制方法,对车体处于不同姿态情况下两种算法的平衡控制性能进行对比分析。实验结果表明,运用互补滤波的PID平衡控制策略能较好的控制车体保持动态平衡,具有较强的鲁棒性,实现了两轮车的自平衡控制,达到了预期目标。

The control strategy of two-wheeled self-balancing vehicles based on motion sensors has been designed, using the PID control method. Based on inertial navigation, the dynamic response performance of attitude determination of two-wheeled self-balancing vehicles using Complementary filter and Kalman filter is synthetically compared. Control performance of the two algorithms when the vehicle is in the case of different attitudes is analyzed and compared. Experimental results show that the PID controller based on complementary filtering can obtain better control effects in the stabilization of vehicles and has good robustness.