基于MPC的AGV导航控制  

AGV Navigation Control Based on MPC

作　　者：张香云 周元华[2] Zhang Xiangyun;Zhou Yuanhua(School of Intelligent Manufacturing,Jingzhou University,Jingzhou,Hubei 434020,China;Mechanical Engineering College,Yangtze University,Jingzhou,Hubei 434023,China)

机构地区：[1]荆州学院智能制造学院,湖北荆州434020 [2]长江大学机械工程学院,湖北荆州434023

出　　处：《机电工程技术》2024年第6期70-73,108,共5页Mechanical & Electrical Engineering Technology

基　　金：湖北省教育厅科学技术研究计划指导性项目(B2022470)。

摘　　要：在构建自动导向小车AGV的结构及运动学模型时,由于建模方式不同,机体坐标系原点选择不同,前驱/后驱和前轮/后轮转向都会导致运动学模型结果不一致,精度较差。因此设计了AGV控制系统并对相关参数进行选取和计算;建立车辆运动学模型并在此基础上设计了AGV导航系统及导航算法,采用MPC优化算法提高轨迹跟踪精度。开展了仿真实验验证,对比AGV控制系统的性能和可靠性。结果表明,改进后的MPC模型在提高轨迹跟踪精度方面的表现比传统控制器模型及其他轨迹跟踪方法效果要好,证明所提方法能够提升车辆行驶的轨迹跟踪控制精度,具有很高的实用价值。When constructing the structure and kinematics model of automatic guided vehicle AGV,due to the different modelling methods,different choices of the origin of the body coordinate system,front/rear drive and front/rear wheel steering will lead to inconsistent kinematics model results and poor accuracy.Therefore,the AGV control system is designed and the relevant parameters are selected and calculated.Kinematics model of vehicle is constructed,the AGV navigation system and navigation algorithm are designed,and the MPC optimization algorithm is used to improve the trajectory tracking accuracy.The performance and reliability of the AGV control system are compared by simulation experiments.The results show that the improved MPC model has better performance than the traditional controller model and other trajectory tracking methods in improving the trajectory tracking accuracy,which proves that the proposed method can improve the trajectory tracking control accuracy of vehicle running and has high practical value.

关 键 词：AGV小车 MPC最优化模型 控制变量 状态量 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]