Semi-Physical Simulation Of Aircraft Brake Control Algorithm

Aircraft brake system as an important part of the aircraft,determines the safety of the plane’s take-off and landing process,and plays a vital role.Because the aviation industry develops fast,the tonnage of aircraft becomes increasingly large,and its speed is more and more rapid,which brings a great challenge for aircraft brake system,so the study of aircraft anti-skid braking control becomes more and more important.In this paper,in order to solve the situation that traditional anti-skid braking control "PD+PBM(Proportion Differentiation+Press Bias Module)" has a poor adaptability and slid in low-speed,combined artificial intelligent control and PID(Proportion Integration Differentiation)control methods,proposed a new Fuzzy-Neural PID strategy that is optimized by using genetic algorithm,thus greatly enhanced the braking performance.To complete the aircraft brake system simulation experiment,the first thing is to set up a corresponding simulation test platform.Relative to the physical simulation,semi-physical simulation has advantages of less investment and high efficiency,while compared with digital simulation,the semi-physical simulation is more reliable and practical.It is an ideal research means for aircraft brake system experiment.Combined the analysis on working principle and structure of aircraft braking system,simultaneously,based on the characteristics of semi-physical simulation technology,the mathematical models of aircraft brake system such as wheel-brake system model,servo-valve model,tire model,airframe model,landing-gear model were built by using Matlab/Simulink.Then,downloading them to the dSPACE through the interface of the RTI-RTW for aircraft brake system simulation founds a simulating platform to test the braking system.In the process,it could adjust the parameters online and display the result data by the ControlDesk.Because the Aircraft-Environment simulation is a part of the hardware in the loop simulation,this paper established plane and terrain visual system model through the Creator3.0.1,and then imported them into the Vega Prime3.0 for visual simulation,and at last,built a complete visual simulation platform combining the MFC.On the basis of the analysis and comparison of the PD+PBM’s,the Fuzzy-Neural PID’s and the Genetic-Fuzzy-Neural PID’s simulation results,the paper found that the Genetic-Fuzzy-Neural PID can solve the traditional control low speed sliding and have a strong adaptability with the runway conditions(dry runway,wet runway and ice runway).This strategy can quickly realize the brake pressure adaptive adjustment,thus improve the braking performance,and obtain a good braking effect.