Quadrotor aircrafts often encounter problems such as low stable attitude accuracy and poor resistance to interference when performing tasks. A neuro-fuzzy PID control algorithm is proposed to adjust the fuzzy rules and membership functions of the original fuzzy PID control. The neuro-fuzzy PID control algorithm is combined with the established dynamic model of the quadrotor aircraft. The traditional PID and fuzzy PID control algorithms are used as comparison algorithms with human interference factors considered to validate the neuro-fuzzy PID controller. The Matlab/Simulink simulation experiment shows that the neuro-fuzzy PID control has better control effect on quadrotor aircrafts than comparison algorithms according to its faster response, higher stable attitude accuracy, and stronger resistance to interference.