Vehicle Path Tracking h∞ Control Method Based on State Feedback

Abstract

The invention relates to a state feedback based vehicle path tracking H-infinity control method, which comprises the steps of firstly acquiring horizontal and vertical coordinates of a reference path, solving a reference course angle, finding a corresponding reference point on the reference path according to the current position of a vehicle, and calculating the position deviation and the course angle deviation between the reference point and a current point of the vehicle; then improving a single-track traditional vehicle dynamic model into a position deviation and course angle deviation based dynamic model, and acquiring a state equation of the system; then taking major influence factors for transverse motion control of the vehicle in the model as bounded disturbance of the system by referring to the yaw rate, and designing a static state feedback controller according to a state feedback H-infinity control law; and finally, converting into a convex optimization problem with linear matrix inequality constraints and a linear objective function, solving a coefficient matrix of the controller by using a linear matrix inequality toolbox, acquiring controller output, namely, a tire rotation angle, and thus realizing path tracking control for the vehicle. The method provided by the invention is applicable to vehicle path tracking control in complex traffic scenes.

Description

technical field [0001] The invention relates to a new vehicle path tracking H∞ control method based on state feedback, which belongs to the field of vehicle path tracking control. Background technique [0002] The intelligentization of automobiles has been developed in full swing in recent years. Google, Baidu, LeTV, Tesla and other companies have invested heavily in the development of intelligent driving technology. In November 2016, China released a roadmap for unmanned driving technology, aiming to achieve highly or fully autonomous driving by 2021. Automobile intelligence can effectively improve the traffic accidents, traffic congestion and pollution emissions of vehicles under the current traffic system. The most important thing is to improve the safety of vehicles. Most traffic accidents are caused by human errors of drivers. Intelligent driving can effectively change this situation. At the same time, intelligent driving can improve the stability, ride comfort and co...

AI Technical Summary

Problems solved by technology

[0003] At present, the most widely used control algorithm is still based on PID control. For ordinary road environments, the control effect is good, but for high-speed roads, large curvature roads and roads with changing driving environments, the adjustment of PID parameters is complicated, and the tracking accuracy is affected by parameters. Large impact, not suitable for unmanned driving in complex traffic environments

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