轻型农用运输AGV的设计与分段模糊控制研究

李诀; 邹大鹏; 王高杰; 任勇

doi:10.12052/gdutxb.200178

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

轻型农用运输AGV的设计与分段模糊控制研究

综合研究 | 更新时间：2026-05-27

- 轻型农用运输AGV的设计与分段模糊控制研究
- A Design of AGV for Miniature Agricultural Transportation and Research on Piecewise Fuzzy Control
- 广东工业大学学报 2022年39卷第1期页码：78-84
- 作者机构：
  
  1. 广东工业大学机电工程学院,广东,广州,510006
  2. 广东顺德创新设计研究院,广东,佛山,528000
  3. 广州柏创机电设备有限公司,广东,广州,511450
- 作者简介：
  
  李诀(1994–)，男，硕士研究生，主要研究方向为单片机开发、AGV控制系统的设计，E-mail：978640059@qq.com
  王高杰(1981–)，男，硕士，主要研究方向为物联网与人工智能，E-mail：67021603@qq.com
- 基金信息：
  
  广东省科技计划项目(2017A010102012);广东省科技特派员企业项目GDKTP2020058900
- DOI：10.12052/gdutxb.200178
  中图分类号： S24
- 纸质出版：2022
- 稿件说明：
移动端阅览
李诀, 邹大鹏, 王高杰, 任勇. 轻型农用运输AGV的设计与分段模糊控制研究[J]. 广东工业大学学报, 2022, 39(1): 78-84.

Li Jue, Zou Da-peng, Wang Gao-jie, et al. A Design of AGV for Miniature Agricultural Transportation and Research on Piecewise Fuzzy Control[J]. 2022, 39(1): 78-84.
李诀, 邹大鹏, 王高杰, 任勇. 轻型农用运输AGV的设计与分段模糊控制研究[J]. 广东工业大学学报, 2022, 39(1): 78-84. DOI： 10.12052/gdutxb.200178.

Li Jue, Zou Da-peng, Wang Gao-jie, et al. A Design of AGV for Miniature Agricultural Transportation and Research on Piecewise Fuzzy Control[J]. 2022, 39(1): 78-84. DOI： 10.12052/gdutxb.200178.

摘要

农用运输自动导引车(Automatic Guided Vehicle

AGV)

作为农业高效、绿色、自动化运输的机械设备

以其低成本、轻型化的设计

成为现代农业机械化的一个重要发展方向。为此

针对农业大棚环境

设计一款基于磁导航的农用运输AGV。对该AGV的运载力进行核算

确定其工作能力

结合设计的磁导航模块

对AGV进行了运动学建模。应用模糊PID控制算法

对AGV的驱动速度进行仿真与实验

结果表明AGV能够在4 s内完成速度的控制响应

并最终做到相对稳定运行

速度误差小于5%。设计分段模糊PID控制算法

对AGV的循迹导引进行仿真与实验

结果表明在不同驱动速度下AGV都能够调节与导航磁条的相对位置误差。稳定运行时

其相对位置误差保持在±7.5 mm以内。

Abstract

Agricultural transport automatic guided vehicle (AGV)

as a high-efficiency

green

automatic transport machinery and equipment

with its low-cost

miniature design

has become an important development direction of modern agricultural mechanization. In view of the agricultural greenhouse environment

an AGV for agricultural transportation based on magnetic navigation is designed. Firstly

the carrying capacity of the AGV is calculated to determine its working capacity. Then

combined with the designed magnetic navigation module

the kinematics model of the AGV is built. The driving speed of the AGV is simulated and tested by using fuzzy PID control algorithm

and the results show that the AGV can complete the speed control response within 4 s

and finally achieve relatively stable operation

with the speed error less than 5%. Finally

the piecewise fuzzy PID control algorithm is designed to simulate and experiment the tracking guidance of AGV

and the results show that the relative position error between AGV and navigation magnetic stripe can be adjusted under different driving speeds

and the relative position error can be kept within ±7.5 mm when AGV runs stably.

关键词

Keywords

references

YU S Y, YE C L, LIU H J, et al . Development of an omnidirectional automated guided vehicle with MY3 wheels [J ] . Perspectives in Science, 2016, 7: 364-368.

ZHANG C B X, HUANG Z Q. Evolution summarization of automated guided vehicles (AGV) [J]. Machine Design and Manufacturing Engineering, 2010, 39(1): 53-59.

LIU M S, HU Y X, LUO X H. Analysis of comprehensive problems based on agricultural transportation [J]. Economic Trade, 2018(17): 38.

SUN X. Development status and trend of light electric agricultural transport machinery [J]. Jiangsu Agricultural Mechanization, 2012(4): 26-27.

DENG W B, WAN H Z. The impact of science and technology innovation and agricultural mechanization on agricultural economic growth in Guangdong province [J]. Journal of Wuyi University (Social Sciences Edition), 2020, 22(4): 67-71.

CHEN Z Q, CAO X, HU X L, et al . High efficient cultivation techniques of potato interplanting with eggplant in greenhouse [J ] . China Vegetables, 2018(5): 101-103.

TAKESHIMA H, HATZENBUEHLER P L, EDEH H O. Effects of agricultural mechanization on economies of scope in crop production in Nigeria [J]. Agricultural Systems, 2020, 177: 102691.

PU B S, CHEN Y K, WANG T, et al . Development status of automated guided vehicle technology and its application and prospect in agriculture [J ] . Jiangsu Agricultural Sciences, 2020, 48(1): 61-65.

BELL J, MACDONALD B A, AHN H S, et al . An analysis of automated guided vehicle standards to inform the development of mobile orchard robots [J ] . IFAC-PapersOnLine, 2016, 49(16): 475-480.

ZHAO C Y, CHEN X K. Study on fuzzy control of an agricultural dedicated AGV with differential steering [J]. Journal of Agricultural Mechanization Research, 2016, 38(11): 123-127.

贺坤. 基于航姿与磁导航传感器融合的四轮转向AGV路径跟踪研究[D]. 镇江: 江苏大学, 2018.

LUO Y J, CHEN X K, GAO Y X. Study on fuzzy control of AGV used in automation of modern agriculture [J]. Industrial Control Computer, 2015, 28(12): 68-71.

KOSTOV M, KOSTOVA V, MARKOSKA R. AGV guidance system simulations with a programmable robotics kit [J]. International Journal of Reasoning-based Intelligent Systems, 2015, 7(1/2): 42-46.

SHANG J, JIANG W G, CAI L T. Design of control system of agricultural automatic guided vehicle with differential steering [J]. Journal of Jiangsu University of Science and Technology (Natural Science Edition), 2011, 25(5): 453-456.

田丽芳. 基于纯滚动转向的采摘机器人轮式AGV系统设计与试验研究[D]. 镇江: 江苏大学, 2016.

王锋. 丘陵山地果园动力底盘的坡地通过性研究[D]. 重庆: 西南大学, 2020.

肖全. 面向3C自动化生产线的AGV结构设计与控制研究[D]. 广州: 广东工业大学, 2018.

鲍金. 基于PID算法的双轮差动式移动机器人定位和导航研究[D]. 沈阳: 东北大学, 2008.

叶甲秋. 自动导向小车(AGV)驱动系统辨识与动态特性分析[D]. 南京: 南京航空航天大学, 2010.

ZHANG J Y. PID control realization of drying system of the finishing line based on MCGS and PLC[C]//2020 2nd International Conference on Applied Machine Learning and Data Science (ICAMLDS 2020). Chengdu: IOP Publishing, 2020, 1629: 012015.

LUO K. Investigation on machinery control system based on fuzzy PID control technology [J]. Applied Mechanics and Materials, 2012, 1999: 130-134.

MA G Z, WU W, DANG G D. Simulation of tracked robot tracking path based on the simulink [J]. Mechanical Research Application, 2017, 30(6): 77-78.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于非线性扰动观测器的永磁同步电机改进滑模控制

基于自适应模糊逻辑系统的一类非线性系统跟踪控制设计

液压伺服系统中模糊-滑模控制器的设计及应用

基于模糊控制的快速控制算法

基于模糊控制的污水处理实验研究