Vehicle trajectory tracking control method based on linear model predictive control algorithm

Abstract

The invention discloses a vehicle trajectory tracking control method based on a linear model predictive control algorithm. The method comprises the following steps: S1, collecting vehicle state information, vehicle positioning information and a reference trajectory; S2, conducting filtering processing on the collected items; S3, acquiring a real-time target point of the vehicle; S4, obtaining a vehicle transverse error and a vehicle course angle error; S5, establishing a linear vehicle dynamics model; S6, obtaining a vehicle steering wheel rotation angle and a vehicle steering wheel rotation speed; S7, respectively carrying out amplitude limiting filtering on the vehicle steering wheel angle and the vehicle steering wheel rotating speed; and S8, sending a result to a controlled vehicle torealize trajectory tracking control. On the basis of the linear vehicle dynamics model, a linear model prediction control algorithm is used, and the real-time performance of control is improved. Meanwhile, the dynamic characteristics of the vehicle and the abrupt change of the vehicle control quantity are fully considered, the vehicle trajectory tracking capability is improved, and the stability of the controlled vehicle during medium-speed and high-speed running is ensured.

Description

technical field [0001] The invention relates to a vehicle control technology, in particular to a vehicle trajectory tracking control method based on a linear model predictive control algorithm, and belongs to the technical field of vehicle automatic driving. Background technique [0002] With the continuous advancement of autonomous driving technology in recent years, the hardware level of various systems corresponding to it has also been greatly improved. [0003] Taking the conventional vehicle trajectory tracking control system as an example, during the actual operation of the system, the trajectory tracking controller in the system calculates the steering wheel angle of the vehicle based on the vehicle positioning information, vehicle status information, etc. , steering wheel speed and other control quantities are sent to the controlled vehicle, and then the trajectory tracking of the vehicle is realized. In the current field of automatic driving, vehicle trajectory tra...

AI Technical Summary

Problems solved by technology

However, after the actual application, the researchers found that the scheme has the following problems: 1. The dynamic characteristics of the vehicle are not considered in the controller, and the trajectory tracking error of the method is relatively large in high-dynamic and high-speed scenarios

2. The PID controller and Fuzzy controller used by the controller are both model-free controllers, and the robustness of the two in trajectory tracking control is poor

However, there are still the following problems in this solution: 1. The trajectory tracking control algorithm is based on the vehicle kinematics model. When the vehicle is running at a medium or high speed, the vehicle dynamics characteristics are obvious. At this time, the trajectory tracking control algorithm The error is very large, and the safe driving of the vehicle cannot be guaranteed.

2. The trajectory tracking control algorithm does not take into account the stability of the control quantity. During the operation of the vehicle, the control quantity is prone to sudden changes, which will cause the vehicle to shake

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