A path-following control method for unmanned vehicles based on soft-constrained quadratic programming MPC

Abstract

The invention relates to a path tracking control method for unmanned vehicles based on soft-constrained quadratic programming MPC. The method first calculates and establishes a new reference path point set P according to known reference path points rset , and then predict the output from the k sampling time to the Np sampling time in the future, and then use the quadratic programming optimization method with soft constraints to calculate the future N c The control increment at each sampling time is obtained, and then the control quantity at the current time is obtained, and the control quantity at the current time is applied to the system, and so on until the end of path tracking. This method replaces the global optimization with local optimization through a rolling optimization strategy, and uses the measured information for feedback correction. The control parameters can be adjusted in real time during the control process, and the path tracking is more accurate.

Description

technical field [0001] The invention relates to the field of path tracking control of unmanned vehicles, in particular to an unmanned vehicle path tracking control method based on soft-constrained quadratic programming 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 vehicles have become a major trend in the development of vehicles. The path following control algorithm of the vehicle has also become a technical research hotspot. [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 cu...

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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

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