Rapid convergence method based on improved complementary filter for attitude of self-balance mobile robot

The invention provides a rapid convergence method based on an improved complementary filter for an attitude of a self-balance mobile robot, and belongs to the technical field of motion control and multi-sensor data fusion. The method is mainly used at an initial motion stage of the mobile robot and enables the mobile robot to be fast stably started. An attitude detection module mainly comprises an MEMS inertial sensor, such as a micro-controller, a gyroscope, an accelerometer, and a magnetometer. According to the method, an angle of inclination estimated by a component of a gravitational field of the accelerometer is taken as auxiliary information; a yaw angle calculated by the magnetometer is obtained through compensation of the angle of inclination; and angular rate information of the gyroscope at three axes is obtained through an euler angle attitude algorithm. Data of the gyroscope and an auxiliary sensor is fused through a complementary filter with parameters flexibly adjusted, and an optimum attitude angle is calculated in time. According to the method, the attitude detection module can quickly respond to an initial attitude angle; noise and drift error can be obviously suppressed; the mobile robot can be quickly stably started; and the stability of the mobile robot is enhanced.