DESIGN OF AIR SUSPENSION SYSTEM BASED ON NEURAL SLIDING MODE CONTROL

In this paper, the vehicle two-degree of freedom suspension model is taken as the system dynamics model to study the semi-active air suspension system. The sky-hook suspension system is selected as the reference model. Based on the error equation of the body motion, a sliding mode controller is designed by using isokinetic approach law. The traditional sliding mode control uses the switching function as the switching control; the inertia of the system causes the control output to produce chattering. Therefore, the neural network control is used instead of the switching function control. The neural network algorithm can approximate the nonlinear system to eliminate the error and reduce the chattering. Finally, the system control model is established in Matlab / Simulink. The simulation results show that the chattering reduction is more stable in the neural sliding mode control.