The intelligentization of flight control systems is an important research direction in the field of aeronautics and astronautics. This paper designs a hybrid intelligent control strategy based on deep reinforcement learning algorithms, achieving precise control of flight attitude. The performance of the control method is verified through simulation experiments, showing significant improvements in attitude stability, anti-interference ability, and control accuracy compared to traditional PID controllers. The experimental results demonstrate that the new method has a significant improvement in control accuracy and system response time, opening up a new direction for the research of intelligent control systems for aircraft.