基于三菱PLC的AGV磁导航PID模糊控制与实现
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摘要
为满足3 C产品自动化生产要求设计了一款实用型AGV,选择以三菱FX-3 U PLC为控制核心,采用磁导航循迹模式,以及差速式驱动方案。针对PLC模糊控制难点,解析了读取RFID卡所必须的Modbus协议,对输入量进行分区模糊处理,设计出基于磁条点位与路径不同来调整PID模糊控制因子的方案。建立运动方程并进行Matlab仿真,最后在生产车间测试该方案。测试结果表明,采用该算法使小车位姿能快速趋于稳定,最大跟踪误差保持在±5°以内,因而可显著提高AGV快速路径跟踪能力,具有较强的鲁棒性。
To meet the automatic production requirements of 3 C products, a practical AGV car was designed.Mitsubishi FX-3 U PLC is taken as the control core, magnetic navigation is chosen as its tracking mode, and differential drive is used for the solutions. To solve the difficulty for fuzzy control of PLC, the Modbus agreement which is necessary to read RFID cards is parsed, fuzzy dispose for the partition input is used and the scheme which can adjust PID fuzzy control factors for itself based on the difference of magnetic stripe and paths is designed. The motion equation was established and carried out by Matlab simulation, finally the designed AGV is tested in the production workshop. Test results show that the algorithm can make the car position quickly tend to be stable, and keep the biggest tracking error remain within ± 5°. So it can significantly improve the fast track tracking ability of AGV car with strong robustness.
To meet the automatic production requirements of 3 C products, a practical AGV car was designed.Mitsubishi FX-3 U PLC is taken as the control core, magnetic navigation is chosen as its tracking mode, and differential drive is used for the solutions. To solve the difficulty for fuzzy control of PLC, the Modbus agreement which is necessary to read RFID cards is parsed, fuzzy dispose for the partition input is used and the scheme which can adjust PID fuzzy control factors for itself based on the difference of magnetic stripe and paths is designed. The motion equation was established and carried out by Matlab simulation, finally the designed AGV is tested in the production workshop. Test results show that the algorithm can make the car position quickly tend to be stable, and keep the biggest tracking error remain within ± 5°. So it can significantly improve the fast track tracking ability of AGV car with strong robustness.
引文
[1]孙灵芳,董学曼,姜其锋.模糊控制的现状与工程应用关键问题研究[J].化工自动化及仪表,2016,43(1):1-5.
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[4]程航.AGV小车轨迹跟踪控制策略的研究[D].合肥:合肥工业大学,2016.
[5]彭光清,楼佩煌.磁导航AGV模糊控制器的研究[J].工业控制计算机,2012,25(9):43-44.
[6]王永鼎,杨家朋.基于RFID的AGV及其在物流配送中心的应用研究[J].微计算机信息,2012(2):93-95.
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[8]郭守春,蒋铁登,周平,等.自适应模糊PID控制器在协调控制系统中的应用[J].测控技术,2014,33(3):75-79.
[9] Chettri P,Chettri A. Ps-ro fuzzy strongly a-irresolute function[J]. ACTA Universitatis Sapientiae, Mathematica, 2017,9(1):260-268.
[2]姚然.基于PLC模糊控制的小型花卉玻璃温室温度控制[D].昆明:昆明理工大学,2015.
[3]黄胄.基于PLC控制的AGV技术研究及其应用[D].上海:华东理工大学,2013.
[4]程航.AGV小车轨迹跟踪控制策略的研究[D].合肥:合肥工业大学,2016.
[5]彭光清,楼佩煌.磁导航AGV模糊控制器的研究[J].工业控制计算机,2012,25(9):43-44.
[6]王永鼎,杨家朋.基于RFID的AGV及其在物流配送中心的应用研究[J].微计算机信息,2012(2):93-95.
[7]马永钧,王彦龙.MODBUS TCP通讯协议在PLC与串口服务器的通讯应用[J].信息通信,2016(10):209-210.
[8]郭守春,蒋铁登,周平,等.自适应模糊PID控制器在协调控制系统中的应用[J].测控技术,2014,33(3):75-79.
[9] Chettri P,Chettri A. Ps-ro fuzzy strongly a-irresolute function[J]. ACTA Universitatis Sapientiae, Mathematica, 2017,9(1):260-268.