基于模糊信息融合的自平衡机器人姿态角补偿方法

为了简便、精确地获得自平衡机器人运行中的状态信息,提出了模糊信息融合的方法对机器人的姿态角进行补偿。首先,根据传感器的工作原理,以及对实验数据的分析建立了陀螺仪漂移误差的数学模型,对其零点随机漂移误差进行了初步的标定。然后根据陀螺仪和倾角传感器各自的误差特性,以及导致这些误差的原因,设计了一个双输入单输出的模糊融合器,将设计的融合器应用到两轮自平衡机器人系统中。实验结果表明系统误差得到了很好的改善,从而表明所设计的模糊融合器是有效的。

Attitude Angle Compensation Method for Self-balancing Robot Based on Fuzzy Information Fusion

To obtain the running state information of the self-based robot simply and precisely, a fuzzy information fusion method is proposed to compensate the attitude angle. First, establish a gyroscope drift mathmatical model according to the working principle of the sensor as well as the analysis of the experimental data and calibrate the zero radom drift preliminarily. Then design a double-input single-output fuzzy fusion according to the respective error characteristics of the gyroscope and the tilt sensor as well as the reason leading to these errors. Then apply the fusion cage to the two-wheeled self-balancing robot system. The results of the experiment show that the system error gets a good improvement, thus indicating that the fuzzy fusion is effective.