A hybrid control method for intelligent vehicle path tracking

Abstract

The invention discloses an intelligent automobile path tracking hybrid control method, and belongs to the technical field of intelligent automobile lateral control. The intelligent automobile path tracking hybrid control method comprises the following steps that step 1, an automobile lateral control preview kinematics model at a low speed is established; step 2, an automobile lateral control dynamic model at a high speed is established; and step 3, a path tracking hybrid controller is designed, the path tracking hybrid controller comprises a lateral controller, a supervisor and a switching stability fuzzy controller, wherein the lateral controller is designed based on PID control and model predictive control, the supervisor determines a tracking mode based on longitudinal vehicle speed, and the switching stability fuzzy controller is designed based on a fuzzy control theory. The intelligent automobile path tracking hybrid control method effectively solves the problem of lateral controlperformance requirements under high-speed and low-speed working conditions of an intelligent automobile, and the easy realization, accuracy and stability of path tracking of the intelligent automobile are improved.

Description

technical field [0001] The invention belongs to the field of motion control of intelligent vehicles, and relates to a lateral control method of an intelligent vehicle, in particular to a path tracking hybrid control method of an intelligent vehicle. Background technique [0002] Lateral motion control is one of the key technologies to realize the autonomous driving of smart cars. Among them, path tracking, that is, to control the vehicle to always drive along the desired path through autonomous steering, while ensuring the driving safety and ride comfort of the vehicle, is oriented to unmanned driving. ultimate goal. Smart vehicles require the lateral motion control system to have accurate, efficient and reliable control performance under a wide range of driving conditions. However, the traditional single control algorithm cannot effectively coordinate the control requirements of the autonomous steering control system under different conditions. At the same time, the autono...

AI Technical Summary

Problems solved by technology

Using the preview PID feedback control method to study the lateral control problem of intelligent vehicles, this control algorithm has the advantages of simple design, good real-time performance and easy implementation under low-speed conditions, but it cannot meet the reliability of intelligent vehicle path tracking under high-speed conditions. sexual demands

The model predictive control method is used to study the lateral control problem of intelligent vehicles. The algorithm first predicts the future output state of the object, and then determines the control action at the current moment, that is, first predicts and then controls; because it has certain predictability, it makes it In high-speed working conditions, it is obviously superior to the traditional PID control system that outputs first and then feedbacks to control, and the control algorithm can constrain vehicle dynamics in high-speed working conditions, not only can quickly and accurately track the target path, but also ensure It ensures the safety and stability of the vehicle, but the design of the controller is relatively complex, the overall calculation is large, and the implementation is relatively difficult.

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