摘要
在自动导引车(AGV)跟踪路径时,路径曲率变化会影响跟踪控制的稳定性和精度。本文基于小车运动学模型,提出一种自适应预测时域模型预测控制器算法,该控制器通过将路径曲率反馈引入模型预测控制(MPC)器中,根据参考路径曲率的变化,自适应地调整预测时域,在提高AGV路径跟踪算法精度的同时还能兼顾AGV小车的稳定性。通过Matlab/Simulink联合仿真,与传统MPC算法进行对比分析,验证了自适应预测时域MPC算法在路径跟踪控制性能方面的优越性,通过实时化改造,将自适应MPC算法在烟厂自主皮带清洗机上进行应用,实际运行效果证明了算法的有效性。
When an automated guided vehicle(AGV)tracks a path,changes in path curvature can affect the stability and accuracy of tracking control.Based on the trolley kinematics model,this paper proposes an adaptive prediction time-domain model prediction controller algorithm,which adaptively adjusts the prediction time domain according to the change of reference path curvature by introducing path curvature feedback into the MPC controller,so as to improve the accuracy of the AGV path tracking algorithm and take into account the stability of the AGV trolley.Through Matlab/Simulink co-simulation,the superiority of the adaptive prediction time-domain MPC algorithm in the path following control performance is verified by the comparison and analysis with the traditional MPC algorithm,and the adaptive MPC algorithm is applied to the autonomous belt cleaning machine of the cigarette factory through real-time transformation,and the actual operation effect proves the effectiveness of the algorithm.
作者
过金超
赵伟航
GUO Jinchao;ZHAO Weihang(School of Electrical and Information Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,Henan,China)
出处
《中国工程机械学报》
北大核心
2025年第5期779-784,共6页
Chinese Journal of Construction Machinery
基金
国家自然科学基金资助项目(51507157)。
