Vehicle Path Tracking Control Based On Model Predictive Control Algorithm

With the transformation and upgrading of the automotive industry,the emergence of a series of innovative technologies has continuously promoted the development of green and intelligent automotive technologies.Among them,autonomous driving technology has become one of the hot research due to its broad development prospects.It can reduce traffic accidents and promote the development of intelligent transportation,so it has become the trend and ultimate goal of intelligent vehicle development.As one of the core technologies in the field of automatic driving,path tracking control is a prerequisite for ensuring vehicle automation.The complex vertical and horizontal coupling relationship of vehicle path tracking makes the vehicle running at high speeds,on low attachment roads,and other extreme conditions such as path tracking travel with poor vehicle stability and low tracking accuracy.Therefore,in order to improve the accuracy and stability of the vehicle’s path tracking,this paper designs a predictive MPC path tracking controller based on the Model Predictive Control(MPC)algorithm combined with the visual preview model theory;PID control theory design longitudinal speed controller to achieve vehicle speed tracking control,design vehicle stability controller based on PID control theory,use the designed stability controller combined with vehicle longitudinal speed controller and lateral path tracking controller to control the vehicle Coupling control is performed,thereby reducing the tendency of the vehicle to track the side slip on a low-adhesion road surface and improving the path tracking performance.The main contents of this article are as follows:(1)Analyze the actual requirements of path tracking control,so as to make a reasonable simplification of the whole vehicle model,and establish a 6-degree-of-freedom vehicle model and a "magic" tire model for four-wheel drive electric vehicles to lay the foundation for the following.(2)Aiming at the problem of poor high-speed path tracking accuracy of vehicles,establish a vehicle preview error model and a simplified vehicle model as a monorail model,and increase the actual road lateral slope as a basis for the prediction model;with different vehicle speeds and roads Curvature is input,preview distance is output,fuzzy rules are used to design preview distance generator;dynamic constraints including vehicle angle and roll are added,model predictive control algorithm is used to solve the optimal control amount,and a preview MPC is established Path tracking controller;due to the reduced accuracy of the model after linearization,combined with the compensation control idea,the forward-looking MPC path tracking lateral controller is used for corner compensation.(3)Establish a PID speed following controller in Matlab/Simulink.The controller obtains the driving torque/braking torque by updating the vehicle speed error in real time to calculate the deceleration or acceleration control of the vehicle;to establish the PID vehicle stability controller,first Calculate the expected yaw rate,and obtain the yaw rate error to calculate the additional yaw moment,so that the driving torque of the left or right wheel can be adjusted accordingly according to the set braking rules.(4)In the joint simulation platform of Matlab/Simulink and Carsim,using the double shift line as the reference path,set the dry pavement and wet pavement respectively to verify the advantages of the preview MPC control algorithm in high-speed path tracking;set the ice and snow pavement,The established lateral path tracking controller and speed controller are combined to verify the simulation of the coupling control through the stability controller.