分布控制的乘坐式仿形采茶原型机研制与试验

doi:10.13305/j.cnki.jts.2022.02.003

茶叶科学 ›› 2022, Vol. 42 ›› Issue (2): 263-276.doi: 10.13305/j.cnki.jts.2022.02.003

分布控制的乘坐式仿形采茶原型机研制与试验

赵润茂^1,2, 卞贤炳¹, 陈建能^1,2,*, 董春旺³, 武传宇^1,2, 贾江鸣^1,2, 毛明¹, 熊永森⁴

1.浙江理工大学机械与自动控制学院,浙江杭州 310018;
2.浙江省种植装备技术重点实验室,浙江杭州 310018;
3.中国农业科学院茶叶研究所,浙江杭州 310008;
4.浙江省农作物收获装备技术重点实验室,浙江金华 321000

收稿日期:2021-09-01 修回日期:2021-10-14 出版日期:2022-04-15 发布日期:2022-04-15
通讯作者: * jiannengchen@zstu.edu.cn
作者简介:赵润茂,男,讲师,主要从事农场环境融合感知与农业机器人研究。
基金资助:
国家自然科学基金（51975537、52105284）、浙江理工大学科研启动基金（20022307-Y）、财政部和农业农村部：国家现代农业产业技术体系资助、浙江省领雁计划项目（2022C02052）

Development and Test for Distributed Control Prototype of the Riding Profiling Tea Harvester

ZHAO Runmao^1,2, BIAN Xianbing¹, CHEN Jianneng^1,2,*, DONG Chunwang³, WU Chuanyu^1,2, JIA Jiangming^1,2, MAO Ming¹, XIONG Yongsen⁴

1. Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou 310018, China;
2. Key Laboratory of Zhejiang Transplanting Equipment Technology, Hangzhou 310018, China;
3. Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China;
4. Key Laboratory of Crop Harvesting Equipment Technology of Zhejiang Province, Jinhua 321000, China

Received:2021-09-01 Revised:2021-10-14 Online:2022-04-15 Published:2022-04-15

摘要/Abstract

摘要： 为提高茶鲜叶采摘机械的自动化水平以及采摘完整率,降低采茶机系统开发成本,缩短开发周期,本研究提出了机采茶蓬面割刀自动仿形方法和分布式快速控制原型机低成本开发方法,研制了仿形采茶样机,并开展室内和田间试验。仿形采茶机采用超声波传感器,感知往复式割刀与茶树蓬面间的距离信息,通过丝杆实现仿形传动;利用Hampel滤波和低通滤波算法对距离信息在线预处理,剔除叶间空缺和割刀振动对茶蓬面真实高度估计的影响。为避免PD控制中数字差分对信号噪声的放大,设计了基于非线性跟踪微分器的仿形控制律PNTD。基于CAN总线网络和代码生成技术,实现多执行单元的分布式快速控制原型机并开展试验,室内多次阶跃测试结果表明,系统响应最大峰值时间为0.14 s,最大超调量为3.6%;田间试验结果表明,割刀覆盖区嫩梢平均采收率92.01%,芽叶完整率82.6%,杂质率6.4%,一芽三叶及以下嫩梢占87.91%。研制的分布式控制仿形采茶原型机作业有效,所采茶鲜叶满足大宗茶机采技术标准和后续加工工艺要求。

关键词: 采茶机, 仿形, 分布式控制, 快速控制原型, 非线性跟踪微分器

Abstract: To better realize the mechanized picking of ordinary fresh tea leaves, reduce the system development cost, and improve the automation level and picking integrity rate, a profiling method of machine-made tea canopy surface cutter and a development method of low-cost and rapid control prototype machine with distributed control were both put forward in this study. Additionally, the profiling tea harvester prototype was developed and the indoor and field tests were launched. The profiling tea harvester uses ultrasonic sensor to sense the distance information from the reciprocating cutter to the tea canopy and realizes profiling transmission through screw rods. Then, Hampel filter and Low-pass filter algorithms are used to preprocess the distance information on-line to eliminate the influence of inter leaf vacancy and cutter vibration on the real height estimation of tea canopy surface. Meanwhile, a proportional nonlinear tracking differentiator (PNTD) control system based on nonlinear tracking differentiator was established in order to avoid the amplification of signal noise by digital difference in conventional PD control and improve the accuracy of profiling of each tea picking unit. Based on CAN bus network and code generation technology, the distributed fast control prototype with multiple execution units was realized and tested. The indoor step test results show that the maximum peak time of this control system was 0.14 s and the maximum overshoot was 3.6%. Finally, to verify the effectiveness of the distributed control profiling tea picking prototype, profiling picking experiments were conducted in the tea garden. The average picking rate of young shoots on the canopy covered by cutter was 92.01%,the integrity rate of buds and leaves was 82.6%, the impurity rate was 6.4%, and the young shoots with at least one bud and three leaves accounted for 87.91%. All the results demonstrate that the proposed methods had good performance and could be used for picking ordinary tea.

Key words: tea harvester, profiling, distributed, rapid control prototyping, nonlinear tracking differentiator

中图分类号:

S571.1

赵润茂, 卞贤炳, 陈建能, 董春旺, 武传宇, 贾江鸣, 毛明, 熊永森. 分布控制的乘坐式仿形采茶原型机研制与试验[J]. 茶叶科学, 2022, 42(2): 263-276. doi: 10.13305/j.cnki.jts.2022.02.003.

ZHAO Runmao, BIAN Xianbing, CHEN Jianneng, DONG Chunwang, WU Chuanyu, JIA Jiangming, MAO Ming, XIONG Yongsen. Development and Test for Distributed Control Prototype of the Riding Profiling Tea Harvester[J]. Journal of Tea Science, 2022, 42(2): 263-276. doi: 10.13305/j.cnki.jts.2022.02.003.

参考文献

[1] 刘仲华, 陈宗懋, 杨亚军, 等. 创新驱动中国茶产业高质量发展——从茶学基础研究到支撑产业发展[J]. 中国茶叶, 2021, 43(2): 1-9.
Liu Z H, Chen Z M, Yang Y J, et al.Innovation drives high-quality development of Chinese tea industry: from basic research of tea science to supporting industrial development[J]. China Tea, 2021, 43(2): 1-9.
[2] 刘仲华. 中国茶叶深加工产业发展历程与趋势[J]. 茶叶科学, 2019, 39(2): 115-122.
Liu Z H.The development process and trend of Chinese tea comprehensive processing industry[J]. Journal of Tea Science, 2019, 39(2): 115-122.
[3] 汤一平, 韩旺明, 胡安国, 等. 基于机器视觉的乘用式智能采茶机设计与试验[J]. 农业机械学报, 2016, 47(7):15-20.
Tang Y P, Hang W M, Hu A G, et al.Design and experiment of intelligentized tea-plucking machine for human riding based on machine vision[J]. Transactions of the Chinese Society for Agricultural Machinery, 2016, 47(7): 15-20.
[4] 权启爱. 采茶机械的研制和我国采茶机械化事业的发展[J].中国茶叶, 2018, 40(8): 14-17.
Quan Q A.Research and development of tea picking machinery and the development of mechanization of tea picking in China[J]. China Tea, 2018, 40(8): 14-17.
[5] 吴雪梅, 张富贵, 吕敬堂. 基于图像颜色信息的茶叶嫩叶识别方法研究[J]. 茶叶科学, 2013, 33(6): 584-589.
Wu X M, Zhang F G, Lv J T.Research on recognition of tea tender leaf based on image color information[J]. Journal of Tea Science, 2013, 33(6): 584-589.
[6] Li Y T, He L Y, Jia J M, et al.In-field tea shoot detection and 3D localization using an RGB-D camera[J]. Computers and Electronics in Agriculture, 2021, 185: 106149. doi: org/10.1016/j.compag.2021.106149.
[7] Chen J, Chen Y, Jin X J, et al.Research on a parallel robot for tea flushes plucking[J]. Advances in Economics, Business and Management Research, 2015. doi: 10.2991/emim-15.2015.5.
[8] 易文裕, 程方平, 邱云桥, 等. 单人采茶机研究现状与发展趋势[J]. 中国农机化学报, 2020, 41(11): 33-38.
Yi W Y, Cheng F P, Qiu Y Q, et al.Research status and development trend of single tea-picking machine[J]. Journal of Chinese Agricultural Mechanization, 2020, 41(11): 33-38.
[9] 韩余, 肖宏儒, 秦广明, 等. 国内外采茶机械发展状况研究[J]. 中国农机化学报, 2014, 35(2): 20-24.
Han Y, Xiao H R, Qin G M, et al.Studies on develop situations of tea-leaf picker both at home and abroad[J]. Journal of Chinese Agricultural Mechanization, 2014, 35(2): 20-24.
[10] Shirai K. Traveling type tea leaf plucking machine: JP2006166710(A) [P].2006-06-29.
[11] 闫晶晶. 仿形采茶机的优化设计及与茶园管理的协调性研究[D]. 合肥: 安徽农业大学, 2019.
Yan J J.Optimization design of profiling tea picking machine and research on coordination with tea plantation management [D]. Hefei: Anhui Agricultural University, 2019.
[12] 王福刚, 杨文君, 葛良全. 嵌入式系统的发展与展望[J]. 计算机测量与控制, 2014, 22(12): 3843-3847, 3863.
Wang F G, Yang W J, Ge L Q.Development and prospects of embedded system[J]. Computer Measurement & Control, 2014, 22(12): 3843-3847, 3863.
[13] 方正, 张淇淳, 齐玉成. 基于DSP的快速控制原型系统[J]. 东北大学学报(自然科学版), 2009, 30(8): 1069-1073.
Fang Z, Zhang Q C, Qi Y C.A rapid control prototyping system based on DSP[J]. Journal of Northeastern University (Natural Science), 2009, 30(8): 1069-1073.
[14] 夏振兴, 代伟, 赵大勇, 等. 桌面机械臂快速控制原型系统设计与开发[J]. 控制工程, 2021, 28(1): 84-92.
Xia Z X, Dai W, Zhao D Y, et al.Design and development of rapid control prototype system oriented towards desktop robot arm[J]. Control Engineering of China, 2021, 28(1): 84-92.
[15] 刘欢欢. 基于dSPACE的履带式机器人运动控制系统设计[D]. 济南: 济南大学,2019.
Liu H H.Design of crawler robot motion control system based on dSPACE [D]. Jinan: University of Jinan, 2019.
[16] 陶岳. 柔顺操作机械臂设计与控制关键技术研究[D]. 西安: 陕西科技大学, 2019.
Tao Y.Research on the design of compliant manipulator and key technologies of control [D]. Xi'an: Shaanxi University of Science and Technology, 2019.
[17] 吴先坤, 李兵, 王小勇, 等. 单人背负式采茶机的设计分析[J]. 农机化研究, 2017, 39(8): 92-96, 101.
Wu X K, Li B, Wang X Y, et al.Design and analysis of single knapsack tea plucking machine[J]. Journal of Agricultural Mechanization Research, 2017, 39(8): 92-96, 101.
[18] 陈纬. 一种便携式采茶机: CN212728090U[P].2021-03-19.
Chen W. The utility model relates to a portable tea picking machine: CN212728090U [P].2021-03-19.
[19] 高可可, 孙江宏, 高锋, 等. 固定式割胶机器人割胶误差分析与精度控制[J]. 农业工程学报, 2021, 37(2): 44-50.
Gao K K, Sun J H, Gao F, et al.Tapping error analysis and precision control of fixed tapping robot[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(2): 44-50.
[20] 高原源, 王秀, 杨硕, 等. 基于CAN总线的播种深度监测评价系统研究[J]. 农业机械学报, 2019, 50(12): 23-32.
Gao Y Y, Wang X, Yang S, et al.Development of CAN-based sowing depth monitoring and evaluation system[J]. Transactions of the Chinese Society for Agricultural Machinery, 2019, 50(12): 23-32.
[21] 安晓飞, 孟志军, 武广伟, 等. 基于CAN总线的谷物产量快速计量系统研发(英文)[J]. 农业工程学报, 2015, 31(s2): 262-266.
An X F, Meng Z J, Wu G W, et al.Development of grain yield monitoring system based on CAN bus technology[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(s2): 262-266.
[22] 胡炼, 罗锡文, 张智刚, 等. 基于CAN总线的分布式插秧机导航控制系统设计[J]. 农业工程学报, 2009, 25(12): 88-92.
Hu L, Luo X W, Zhang Z G, et al.Design of distributed navigation control system for rice transplanters based on controller area network[J]. Transactions of the Chinese Society of Agricultural Engineering, 2009, 25(12): 88-92.
[23] 谢云德, 龙志强. 高精度快速非线性离散跟踪微分器[J]. 控制理论与应用, 2009, 26(2):127-132.
Xie Y D, Long Z Q.A high-speed nonliner discrete tracking-differentiator with high precision[J]. Control Theory & Applications, 2009, 26(2): 127-132.
[24] 韩京清. 自抗扰控制技术[J]. 前沿科学, 2007(1): 24-31.
Han J Q.Auto Disturbances rejection control technique[J]. Frontier Science, 2007(1): 24-31.
[25] 杜超. 感应电机驱动系统的自抗扰控制[D]. 西安: 西安理工大学, 2020.
Du C.Active disturbance rejection control for an induction motor drive system [D]. Xi'an: Xi'an University of Technology, 2020.
[26] Zhu Y P, Wu C Y, Tong J H, et al.Deviation tolerance performance evaluation and experiment of picking end effector for famous tea[J]. Agriculture, 2021, 11(2): 128-128.
[27] 中华人民共和国农业部. 采茶机作业质量: NY/T 2614—2014 [S]. 北京: 中国农业出版社, 2015.
Ministry of Agriculture of the People's Republic of China. Operating quality for tea picking machines: NY/T 2614-2014 [S]. Beijing: China Agricultural Press, 2015.
[28] 李修华, 颜森, 高娜娜, 等. 基于超声波传感器的小麦追肥精准评估系统研究[J]. 农业机械学报, 2020, 51(s1): 203-209.
Li X H, Yan S, Gao N N, et al.Accurate evaluation system for wheat topdressing based on ultrasonic sensor[J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 51(s1): 203-209.
[29] 付根平, 杨尘宇, 张世昂, 等. 香蕉园机器人导航的激光与超声波组合测距方法研究[J]. 农业机械学报, 2021, 52(5): 159-168.
Fu G P, Yang C Y, Zhang S A, et al.Research on laser and ultrasonic combined ranging method for robot navigation at banana plantation[J]. Transactions of the Chinese Society of Agricultural Engineering, 2021, 52(5): 159-168.
[30] 姜增如. 控制系统建模与仿真—基于MATLAB/Simulink的分析与实现[M]. 北京: 清华大学出版社, 2020.
Jiang Z R.Control ssystem modeling and simulation: analysis and implementation based on MATLAB/Simulink [M]. Beijing: Tsinghua University Press, 2020.

分布控制的乘坐式仿形采茶原型机研制与试验

Development and Test for Distributed Control Prototype of the Riding Profiling Tea Harvester

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

Metrics

本文评价

推荐阅读 10

[1]	韩余, 肖宏儒, 秦广明, 陈东胜, 宋志禹, 丁文芹, 梅松. 自走式采茶机液压系统的设计和试验研究[J]. 茶叶科学, 2014, 34(6): 548-556.
[2]	邵陆寿. 4C─80型微电机驱动采茶机的设计[J]. 茶叶科学, 1996, 16(01): 9-12.
[3]	蒋有光. 采茶机切割器系统的优化设计[J]. 茶叶科学, 1986, 6(02): 47-52.
[4]	殷鸿范. 国內外采茶机研究概况及几个问題的探讨[J]. 茶叶科学, 1965, 2(02): 66-71.
[5]	殷鸿范. NIC型电动採茶机组试验初报[J]. 茶叶科学, 1964, 1(01): 85-86.