UAV component testing system, mainly for a large unmanned aerial vehicle components for performance testing and test validation. The control parameters of the system have strong coupling between temperature, pressure and flow. In order to compensate for the shortcomings of conventional control methods, a forward multi-layer decoupling controller based on PID neural network is designed, and the weight of neural network is trained by genetic algorithm. This algorithm is simulated under MATLAB, and the decoupling control effect is ideal. Then, it is verified by the Aviation product testing system. The control method can meet the design requirements and supported the development of the relevant model.