Research On Trajectory Tracking Of Unmanned Vehicle Based On Model Predictive Control

Unmanned driving technology is one of the most popular research directions at present,representing the highest level of current science and technology.It mainly includes three modules: environment perception,decision planning,and motion control.Trajectory tracking is the main research content of motion control.One of the core of unmanned driving technology.Therefore,the study of vehicle trajectory tracking is of great significance to the realization of unmanned driving technology.In this paper,based on the model predictive control algorithm,the problem of unmanned vehicle trajectory tracking is further studied.The specific research content is as follows:First,for the driverless trajectory tracking problem,a vehicle kinematics model considering the geometric constraints of motion is established;a three-degree-of-freedom nonlinear vehicle dynamics model is established based on the dynamic characteristics and the magic formula tire model;the basic model predictive control algorithm is introduced Principle,the algorithm process is deduced in detail.Secondly,according to the model predictive control algorithm,it can deal with the problem of multiple constraints.First,a kinematics-based model predictive controller is designed,which can be suitable for trajectory tracking in low-speed scenarios.At the same time,in order to solve the problem of kinematic model mismatch at medium and high speeds,a dynamics-based model predictive controller is designed.After simulation analysis,it has better tracking effects at different speeds.Finally,aiming at the accuracy and stability of trajectory tracking,an improved model predictive controller is proposed,which changes the size of weight matrix according to the curvature of reference trajectory.Through the simulation analysis of Car Sim / Simulink joint simulation platform,the results show that the improved model predictive controller at different speeds has higher tracking accuracy and stability,and has better robustness to different attached roads.