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In order to solve the problem that the control system of traditional four rotor UAV is disturbed by the outside world and can't avoid the obstacles in time, which leads to the low control accuracy, the control system design of four rotor UAV Based on deep learning is proposed. According to the overall structure of the four rotor UAV control system, the ultrasonic ranging module is added. According to the system hardware block diagram, TMS320F28335 main control chip is used to realize the key situation intelligent analysis. Taking the control object of the cascade PID controller as the attitude angle of the UAV, the motor speed is controlled. According to the PWM signals of different duty cycle sent by DSP, the flight attitude of UAV is changed, and according to the driving principle of actuator, the balance state of UAV during flight is ensured. Using infrared remote control system, using encoder / decoder to control IC chip, using ts0p1738 infrared receiver, suitable for infrared remote control data transmission. The depth learning target control model is constructed, and the pixel size is calculated by using the method of location matrix and the principle of triangle similarity. The distance between the obstacle and the current position of UAV is obtained to avoid the interference of external obstacles. The adaptive extended Kalman filter technology can effectively reduce the measurement error of UAV automatic control system and accurately track the maneuvering target. According to the results of system debugging, the pitch angle, heading angle and roll angle controlled by the system are consistent with the actual values, which is of great significance to deal with unexpected group events.