中国农机化学报2026，Vol.47Issue(2)：157-167,176,12.DOI:10.13733/j.jcam.issn.2095-5553.2026.02.022
基于ILA—LQR—PID的田间智能作业车路径跟踪控制
Path tracking control of field intelligent operation vehicle based on ILA—LQR—PID
摘要
Abstract
When intelligent vehicles operate in fields,they often experience slippage due to low friction coefficients caused by slippery ground conditions.In order to improve the efficiency of intelligent vehicle operations in the field,reduce slippage on wet surfaces,and address the challenge of determining control algorithm parameters,this study proposes a control method called Incomprehensible but Intelligible in time logics(ILA)for determining parameters of an LQR—PID controller,termed ILA—LQR—PID,which employs a strategy for path tracking control.Firstly,the dynamic model of the intelligent vehicle is established.Then,feedforward LQR lateral tracking controller,PID longitudinal velocity tracking controller,steering slip controller,and braking slip controller are designed.Subsequently,the core parameters of each controller are determined by using the logical optimization algorithm ILA.To validate the feasibility of the strategy,joint simulation experiments are conducted by using MATLAB/Simulink and Carsim.The results show that under the conditions of a vehicle speed of 10 km/h and a friction coefficient of 0.9,ILA—LQR—PID algorithm strategy compares the control method COA—LQR—PID for determining controller parameters with the original LQR—PID and the Coati Optimization Algorithm(COA)method,the average speed error,maximum lateral error and arrival error in different environments are reduced by 88.1%,85.8%,98.6%,and 6%,41.1%,57.3%,respectively.Under the conditions of a vehicle speed of 10 km/h and a friction coefficient of 0.3,they are reduced by 61.1%,76.9%,97.7%,and 28.5%,36.3%,58.2%,respectively.Under conditions of a vehicle speed of 30 km/h and a friction coefficient of 0.9,they are reduced by 44.8%,92.2%,99.1%,and 26.9%,77.8%,91.5%,respectively.Moreover,the errors are all in the centimeter range,meeting the requirements of field operations,and providing technical support for smart agriculture.关键词
田间智能作业车/路径跟踪/LQR控制/PID控制/逻辑优化算法Key words
field intelligent operation vehicle/path tracking/LQR control/PID control/logical optimization algorithms分类
农业科技引用本文复制引用
Miao Kai,Ren Lisheng,Wang Fang..基于ILA—LQR—PID的田间智能作业车路径跟踪控制[J].中国农机化学报,2026,47(2):157-167,176,12.基金项目
河北省省级重点研发计划项目(19220119D) （19220119D）
