In order to solve the problems of slow smooth control response, poor adaptive ability, and weak anti-interference ability of the UAV flight control system,this article analyzes the principle of UAV flight control system and establishes a drone flight control model, under the condition of cascade fuzzy PID control, using the iterative optimization ability of PSO algorithm, the quantization factor, scale factor and initial PID parameters in fuzzy control are determined. PID parameters are adjusted online through fuzzy control, so that the parameters in the smooth control are kept optimized at all times.Therefore,a cascade fuzzy PID flight control system based on particle swarm optimization is designed. The experimental results show that: When the values of the quantization factors e and ec are 3 and 0.75, and the values of the scale factors k1, k2, and k3 are 0.5, 2, and 0.5, respectively, the system stability is optimal.compared with cascade PID control and cascade fuzzy PID control, the control system optimized by PSO has better control accuracy and stability, and can better improve the performance of the system and meet the flight requirements of fast and efficient leveling.