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The application frequency of quadcopter drones is increasing, and the application scenarios are becoming more complex, which puts higher requirements on their flight attitude control performance. The existing methods for attitude control of quadcopter drones may lead to divergent or oscillatory flight behavior, making it difficult to achieve the desired position and attitude. Therefore, based on the backstepping sliding mode algorithm, a self-adaptive control method for the flight attitude of quadcopter unmanned aerial vehicles is designed. Based on the structure of a quadcopter drone, a dynamic model of the quadcopter drone is constructed. MEMS inertial sensors are used to measure the current position and attitude of the quadcopter drone, and the Kalman filtering algorithm is combined to decouple the flight attitude angle. According to the flight attitude control requirements of the quadcopter drone, a controller is designed using the backstepping sliding mode algorithm, which measures the flight attitude angle roll angle The decoupling calculation results of pitch angle and yaw angle are used as inputs to the controller, and the output results of the controller are the flight attitude control parameters, achieving effective control of the flight attitude of quadcopter unmanned aerial vehicles. Experimental data shows that after applying the method proposed in this article to control the flight posture of quadcopter unmanned aerial vehicles, the control results are basically the same as the expected position and posture. The maximum deviation between roll angle, pitch angle, and yaw angle does not exceed 4 °, indicating high control accuracy.