Unmanned vehicle path tracking control method based on soft constraint quadratic programming MPC

Abstract

The invention relates to an unmanned vehicle path tracking control method based on a soft constraint quadratic programming MPC. The method comprises the steps that firstly, a new reference path pointset Prset is calculated and established according to known reference path points; secondly, output from a kth sampling point to future Np sampling moments is predicted; thirdly, a control increment offuture Nc sampling moments is calculated by using an optimization method with soft constraint quadratic programming, and therefore a control amount at the current moment is obtained; finally, the control amount at the current moment is applied to a system, and the steps above are repeated until path tracking is completed. According to the method, through a rolling optimization strategy, global optimization is replaced by local optimization, feedback correction is conducted by utilizing actually-measured information, control parameters can be adjusted in the control process in real time, and path tracking is more accurate.

Description

Technical field [0001] The invention relates to the field of unmanned vehicle path tracking control, in particular to an unmanned vehicle path tracking control method based on soft constraint secondary planning MPC. Background technique [0002] With the increase in the number of cars in the world, the urban road environment is becoming more and more complex. In order to improve the safety and efficiency of vehicle driving, intelligent and unmanned has become a major trend in automobile development. Vehicle path tracking control algorithm has also become a technical research hotspot. [0003] The existing algorithm can perform tracking control according to the existing path. To be precise, it divides the path into several points and controls the vehicle to pass through these points one by one. The current control amount cannot be adjusted according to the change trend of the parking path during the whole process. And most of the current researches consider controlling under the co...

AI Technical Summary

Problems solved by technology

[0003] The existing algorithm can perform tracking control according to the existing path. To be precise, the path is divided into several points and the vehicle is controlled to pass through these points one by one. During the whole process, the current control amount cannot be adjusted according to the changing trend of the parking path. And most of the current research considers the control under the condition of constant vehicle speed, but the vehicle speed cannot be completely constant during the actual driving process, which brings difficulties to this type of algorithm

Images