Research On Intelligent Vehicle Lateral Motion Control Based On Model Predictive Control Algorithm

The development of intelligent transportation systems can effectively alleviate road congestion,reduce traffic accidents,improve energy efficiency,and reduce environmental pollution.As a significant portion of the intelligent transportation system,intelligent vehicles integrate technologies such as environment perception,planning and decision-making,and motion control.Efficient and stable vehicle lateral motion control system is a necessary condition for the realization of vehicle intelligence and practicality.The thesis takes the lateral motion control system of intelligent vehicles as the research object,and studies the proof of the closed-loop stability of the vehicle’s lateral motion model predictive controller while ensuring tracking accuracy and lateral stability under high-speed and low-road adhesion coefficient conditions.The main research work is as follows:1.Use the magic formula to construct the vehicle tire model,determine the linear working range of the tire and simplify the tire force in the linear working area,and establish the vehicle dynamics model based on reasonable assumptions.2.In order to ensure the lateral stability of the intelligent vehicle during path tracking at high speed and under low-adhesion road conditions,this paper designs the intelligent vehicle lateral motion controller,which is based on model predictive control algorithm.The predictive model of the controller is obtained by linearizing and discretizing the vehicle dynamics model.At the same time,the yaw rate and the center of mass slip angle,which characterize stability,are incorporated into the objective function and constraints of the controller to ensure the lateral stability of the vehicle.This avoids the situation that the vehicle loses its tracking ability due to the front axle slips or loses its stability due to the rear axle slips during steering.The effectiveness of the controller is verified by building a Car Sim and Matlab/Simulink joint simulation platform under high-speed driving conditions and low-adhesion pavement coefficient driving conditions.3.Aiming at the problem that the intelligent vehicle lateral motion controller based on the model predictive control algorithm lacks proof of closed-loop stability,this paper adopts a model predictive control algorithm based on the control Lyapunov function to control the lateral motion of the vehicle.Based on the standard model predictive control algorithm,the control Lyapunov function shrinkage constraint is constructed,so that the model predictive control algorithm can inherit the stability of the state feedback control law based on the Lyapunov function design.The algorithm combines the control Lyapunov function theory with the model predictive control algorithm,which not only ensures the stability of the closed-loop system,but also makes full use of the rolling optimization technology of the model predictive control algorithm to obtain better control performance.The closed-loop stability of the system is verified by building the Car Sim and Matlab/Simulink joint simulation platform under the working conditions of straight line and double shift line.