The RBF Sliding Mode Control And Stimulation Research On Active Suspension Of The Three-axle Vehicle

With the development of the social economy and the progress of science and technology,the multi-axle vehicle plays an increasingly important role in the transportation of goods and construction of the facilities.Due to the poor driving environment,the cross-country performance and ride comfort of multi-axle vehicles have attracted much attention.The suspension system is an important part of the vehicle,which affects the performance of the vehicle.Therefore,it is of great significance to study the active suspension system of the three-axle vehicle and its control method.This paper combines the national key research and development project ”The key technology research of special chassis and suspension of high mobile emergency rescue vehicles(including fire-fighting vehicles)”(project number: 2016YFC0802900).In order to improve the ride performance and handling stability of the vehicle,the sliding mode variable structure controller and the RBF neural network sliding mode variable structure controller for the active suspension system are designed,and The active suspension system of the three-axle vehicle is studied in terms of control and simulation.First,This paper summarizes the research status and development trend of suspension system and its control methods,and puts forward its research purpose and research content.Secondly,a random road excitation model is established,and based on the physical model of nine-degree-of-freedom of the three-axle vehicle,the state equation of the active and passive suspension system and the skyhook reference model are established,and the performance evaluation index of suspension system is also given.Thirdly,an error dynamic model based on the reference model is established.Based on this model,a sliding mode variable structure controller for the active suspension system of the three-axle vehicle is designed.Fourthly,in order to reduce the chattering problem of sliding mode structure more effectively,the RBF neural networkis selected to optimize the sliding mode variable structure control.Finally,the passive suspension system model,the active suspension system model based on sliding mode variable structure control and the active suspension system model based on RBF neural network optimization for sliding mode control of the threeaxle vehicle is established in MATLAB/Simulink.According to the vertical,pitching and tilting acceleration of the body,suspension dynamic displacement and tire dynamic deflection,active suspensions under two control methods are compared with the passive suspension.The simulation result shows that the two control methods can improve the stability of the three-axle vehicle and improve the ride performance effectively.