基于MPC与Stanley的农机路径跟踪融合控制算法
Path tracking fusion control algorithm of agricultural machine based on MPC and Stanley
刘文龙 1姜明耀 1王晨旭 1徐伟东1
作者信息
- 1. 东北石油大学秦皇岛校区电气信息工程系,河北秦皇岛 066004
- 折叠
摘要
针对智能农机的路径跟踪问题,基于模型预测控制(MPC)与Stanley控制提出一种融合控制算法.在农机运动学模型基础上,运用MPC算法设计路径跟踪控制律.在MPC算法的基础上通过权重系数与Stanley算法进行融合,并采用模糊规则对权重系数进行动态修正.搭建Carsim与Matlab/Simulink联合仿真平台,分别以不同速度对直线路径与圆形路径进行跟踪实验.结果表明,文中算法的控制性能优于常规MPC算法,在跟踪过程的前半段更为迅速,在跟踪过程的后半段更加平稳,直线路径跟踪误差在±2.5cm以内,特别适于农机初始位置偏差较大以及行驶速度较高的应用场合.
Abstract
A fusion control algorithm based on Model Predictive Control(MPC)and Stanley control is pro-posed to solve the problem of path tracking of intelligent agricultural machine.Based on the kinematic mod-el of agricultural machine,the path tracking control law is designed using MPC algorithm.On the basis of MPC algorithm,the weight coefficient is fused with Stanley algorithm,and the fuzzy rules are used to dy-namically correct the weight coefficient.The Carsim and Matlab/Simulink co-simulation platforms are built,and the linear path and circular path are tracked at different speeds.The results show that the control per-formance of the proposed algorithm is better than the conventional MPC algorithm,which is faster in the first half of the tracking process and more stable in the second half of the tracking process.The linear path tracking error is less than±2.5cm,which is suitable for large deviation of the initial position of agricultural machine and high driving speed applications.
关键词
智能农机/模型预测控制/Stanley控制/模糊规则/路径跟踪Key words
intelligent agricultural machine/model predictive control/Stanley control/fuzzy rule/path track-ing引用本文复制引用
基金项目
东北石油大学青年科学基金(2020QNQ-04)
出版年
2024
NETL
NSTL
万方数据