Research On The Hybrid Control Method For Path Tracking Of Intelligent Vehicle

Intelligent vehicle,as an important mean to improve traffic safety and efficiency,has become the main development direction of automobile technology in the world.Path tracking control is one of the key technologies to realize the autonomous driving of intelligent vehicles.However,under actual working conditions,the driving conditions of intelligent vehicles are highly time-varying and uncertain,which brings great challenges to the path tracking control.From the perspective of safety and stability of intelligent vehicle control,different working conditions should have different control objectives and emphases,In addition,The single control algorithm has its own limitations and specific conditions of use.It can not take into account the multi-condition characteristics in the process of intelligent vehicle path tracking control and coordinate the control performance requirements under different conditions.Therefore,the traditional single control algorithm can not effectively coordinate the performance requirements for path tracking of intelligent vehicles under different steering conditions,and it is difficult to achieve the best performance for the target path tracking.On account of this,combined with the different system characteristics of intelligent vehicle in high speed and low speed steering conditions,a hybrid path tracking control is proposed based on the theory of PID control,model predictive control(MPC)and fuzzy control.The purpose of this paper is to improve the path tracking performance of intelligent vehicle by combining the advantages of multiple intelligent control strategies under different speed conditions,The main research contents are as follows:(1)Firstly,the vehicle preview kinematics model,vehicle dynamics model and tire model are established.According to the cornering characteristics of tire model,the constraints range of cornering angle of tire for stable running of vehicle are analyzed.Then,on this basis,the PID path tracker based on speed compensation and the path tracking controller based on MPC theory are designed respectively.On the basis of analyzing the advantages and disadvantages of PID control and model predictive control,Combining the PID control with the model predictive control,and the control effect of the two control algorithms under variable speed path tracking is obtained through simulation analysis.At last,a hybrid switching control method of intelligent vehicle path tracking in low-speed mode using PID control and high-speed mode using MPC control is proposed.The results of the joint simulation on the platform of Matlab/Simulink andCarsim show that,according to different modes,the two control algorithms only switch the output values of different controllers at the switching point,which is prone to large jumps in the output values of the controllers,causing system disturbance and transient response,seriously affecting the lateral stability of the vehicle,and at the non-switching point,the hybrid control has better path tracking control effect than single PID control and single MPC control.(2)In order to solve the lateral instability problem caused by switching between different control algorithms,a switching stable fuzzy controller is designed based on the theory of fuzzy control,aiming at reducing the large jump of the front wheel of the lateral controller output caused by switching between different control algorithms.The simulation results show that the switching stability fuzzy controller realizes the smooth and stable switching output of the lateral control system,and improves the tracking accuracy and stability of the path tracking system.(3)In order to verify the effectiveness of the hybrid path tracking controller in the real environment,the real vehicle experiment was carried out on the Haval H8 intelligent vehicle platform.The experimental results show that the hybrid control method proposed in this paper can satisfy the driving requirements under different conditions of high and low speed in the path tracking process,and can realize the smooth and stable switching between the two control algorithms.So it can satisfy the control performance of the system under different conditions,and achieve the purpose of global optimization,it also can obtain better control performance than a single control algorithm,which is superior to the traditional single PID control and MPC path tracking control,and improve the accuracy of path tracking and vehicle driving stability.