Design optimization and simulation of active direct feedback and full-state feedback control method on railway vehicle
In order to solve the problems of high-speed trains,such as the deterioration of dynamic performance and the decline of running stability under long operating distance,an active direct feedback and full-state feedback control method are proposed.A nonlinear model of the whole vehicle is established based on Simpack simulation platform to simulate the real running state of the vehicle and the signals collected by real sensors.Based on the MATLAB platform,the vertical linear model of the vehicle is estab-lished,and the Kalman filter is used to establish a state observer with reference to the linear model,and the vehicle state quantity is restored in real time according to the set number and type of sensor signals.Using the Sky-Hook control based on direct signal feedback and the Linear Quadratic Regulator(LQR)and H oo control method based on full state feedback respectively,the verti-cal full state feedback control algorithm of the whole vehicle is designed to realize the vertical active control of the secondary sus-pension of the vehicle.Aiming at the straight line operation and fault conditions,the SIM AT joint simulation method is used to simulate and analyze the signal acquisition,state observation and active control loop,and evaluate the effectiveness of the method.Simulation results show that the state observer can realize more accurate state observation of the whole vehicle.Combined with the state observation results,all three control methods can improve the running stability of the vehicle under normal operating conditions,and the vehicle body stability index can be reduced by 19%at most,and the maximum vibration acceleration can be reduced by 54%.When the air spring of the front bogie fails,the active control method can ensure the vehicle to run safely to a certain extent.With the Hoo control method,the maximum pitching angle during the simulation time is reduced by 83%.
state observeractive controlrobustness controladaptive bogie