Modeling and parameter identification of verification systems using stochastic configuration networks

The gas flow verification system with positive pressure sonic nozzle is calling for high requirements on the stability of gas source pressure. It is difficult to guarantee the stagnation cabin pressure be controlled within its targeted range, because of varying boundary conditions. To solve the above problems, this paper presents a modeling method based on mechanism and data-driven for gas flow verification system with the positive pressure sonic nozzle. The stochastic configuration network is used to dynamically identify parameters in the mechanism model. After substituting the identification results into the model, the RMSE of the pressure and temperature in the stagnation cabin obtained from the simulation and the actual data are 1.26 × 104 and 2.64 × 104, respectively. Considering the dead zone of the regulating valve and the replacement of regulating valve in the actual operation, the model is analyzed by disturbance experiment. Experimental results show that the dynamic mathematical model could reflect the changing trend of the pressure in the pressure regulating process and prove its effectiveness.