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基于模糊控制的设施菜心生产环境管控模型及系统

毛远洋, 陈芳玲, 卞智逸, 肖德琴, 周敏

毛远洋, 陈芳玲, 卞智逸, 等. 基于模糊控制的设施菜心生产环境管控模型及系统[J]. 华南农业大学学报, 2024, 45(1): 127-136. DOI: 10.7671/j.issn.1001-411X.202209034
引用本文: 毛远洋, 陈芳玲, 卞智逸, 等. 基于模糊控制的设施菜心生产环境管控模型及系统[J]. 华南农业大学学报, 2024, 45(1): 127-136. DOI: 10.7671/j.issn.1001-411X.202209034
MAO Yuanyang, CHEN Fangling, BIAN Zhiyi, et al. Management model and system based on fuzzy control for production environment of facility flowering Chinese cabbage[J]. Journal of South China Agricultural University, 2024, 45(1): 127-136. DOI: 10.7671/j.issn.1001-411X.202209034
Citation: MAO Yuanyang, CHEN Fangling, BIAN Zhiyi, et al. Management model and system based on fuzzy control for production environment of facility flowering Chinese cabbage[J]. Journal of South China Agricultural University, 2024, 45(1): 127-136. DOI: 10.7671/j.issn.1001-411X.202209034

基于模糊控制的设施菜心生产环境管控模型及系统

基金项目: 广东省重点领域研发计划(2019B020214005);广州市科技计划(202206010116)
详细信息
    作者简介:

    毛远洋,博士研究生,主要从事动植物生产监测与管控的数据智能处理研究,E-mail: 595516799@qq.com

    通讯作者:

    肖德琴,教授,博士,主要从事动植物生产监测与管控、农业物联网与产业大数据智能处理研究,E-mail: deqinx@scau.edu.cn

  • 中图分类号: S126;S636

Management model and system based on fuzzy control for production environment of facility flowering Chinese cabbage

  • 摘要:
    目的 

    为实现设施菜心生产环境的实时监控和精准调控,设计一种基于模糊控制的设施菜心生产环境管控模型及系统。

    方法 

    采用物联网设备实时监测菜心各生长阶段(种子发芽期、叶片生长期、菜薹形成期)的环境因子(空气温度、土壤温度、土壤湿度和土壤电导率),将参数的监测值与适宜范围进行对比,获得各环境因子的偏差及变化率。管控模型利用模糊推理与定性分析结合的方法优化环境因子控制量,确定环境调控设备的调控决策,达到对环境因子的精准调控。

    结果 

    管理模式对比试验表明:在菜心3个生长阶段,管控系统模式的平均调控实时性指标分别为0.10、0.17和0.18,平均准确性指标分别为0.78、0.68和0.74;人工管理模式的平均调控实时性指标分别为0.37、0.41和0.43,平均准确性指标分别为0.31、0.34和0.30。管控系统的平均实时性和准确性与人工管理模式相比分别有62.50%和1.34倍的提升。

    结论 

    管控系统模式实现了菜心生产环境信息的实时获取与精准调控,能帮助用户更好地进行设施菜心的生产管理。

    Abstract:
    Objective 

    To achieve real-time monitoring and precise regulation of the growing environment of facility flowering Chinese cabbage, a growing environment management model and system based on fuzzy control was designed.

    Method 

    The system used Internet of Things equipment to monitor environmental factors (atmospheric temperature, soil temperature, soil moisture, and soil electrical conductivity) information in real-time at seed germination period, leaf growth period and stalk formation period, and compared the monitored values with the values of suitable range of the parameters to obtain the deviation of each environmental factor and its change rate. The management model used a combination method of fuzzy reasoning and qualitative analysis to optimize the control amount of environmental factors, determined the regulation decision of environmental regulation equipment, and achieved the precise regulation of environmental factors.

    Result 

    The comparison tests of the management modes showed that the average real-time control performance of the control system mode was 0.10, 0.17, and 0.18, and the average accuracy was 0.78, 0.68, and 0.74 respectively in the three growth stages; The average real-time control performance of the manual management mode was 0.37, 0.41 and 0.43, and the average accuracy was 0.31, 0.34 and 0.30, respectively. The average real-time performance and accuracy of the management system were improved by 62.50% and 1.34 times respectively compared with the manual management mode.

    Conclusion 

    This management system can realize the real-time acquisition and accurate regulation of the production environment information, and help users better manage the production of the facility flowering Chinese cabbage.

  • 图  1   设施菜心管控模型及系统框架

    Figure  1.   Framework of the management model and system for protected flowering Chinese cabbage

    图  2   管控平台界面

    Figure  2.   Control platform interface

    图  3   模糊控制模型结构

    Figure  3.   Structure of fuzzy control model

    图  4   空气温度和土壤温度变化曲线

    Figure  4.   Variation curves of atmospheric temperature and soil temperature

    图  5   土壤湿度(a)和土壤电导率(b)变化曲线

    浅蓝色为种子发芽期,浅绿色为叶片生长期,浅黄色为菜薹形成期

    Figure  5.   Variation curves of soil moisture (a) and soil electrical conductivity (b)

    Light blue is for seed germination period, light green for leaf growth period, light yellow for stalk formation period

    图  6   实时性试验结果

    Figure  6.   Results of real-time experiments

    图  7   准确性试验结果

    Figure  7.   Results of accuracy experiments

    表  1   环境因子适宜范围

    Table  1   Suitable range of environmental factors

    生长时期
    Growth period
    θ空气/℃
    Atmospheric temperature
    θ土壤/℃
    Soil temperature
    土壤相对湿度/%
    Soil relative moisture
    σ土壤/(mS·cm−1)
    Soil electrical conductivity
    种子发芽期
    Seed germination period
    25~30 25~30 60~80 0.1~0.2
    叶片生长期
    Leaf growth period
    20~25 20~35 70~90 0.2~0.3
    菜薹形成期
    Stalk formation period
    20~25 20~25 60~80 0.3~0.4
    下载: 导出CSV

    表  2   传感器具体信息

    Table  2   Specific information of sensors

    传感器类型
    Sensor type
    数据传输方式
    Data transmission method
    型号
    Model
    详情
    Detail
    大气温、湿度
    Atmospheric temperature and humidity
    RS-485 威盟士VMS-3002-WS 温度精度为±0.5 ℃、相对
    湿度测量精度为±3%
    土壤温、湿度
    Soil temperature and humidity
    RS-485 威盟士VMS-3001-TR-*-N01 温度测量精度为±0.5 ℃、
    相对湿度测量精度为±3%
    土壤电导率
    Soil electrical conductivity
    RS-485 威盟士VMS-3001-TR-*-N01 分辨率为1 µS·cm−1、土壤
    电导率测量精度为±3% FS
    下载: 导出CSV

    表  3   模糊控制状态1)

    Table  3   Fuzzy control states

    EE
    PZN
    PBPBPBPM
    PMPBPMPS
    PSPMPMZ
    ZPMZZ
    NSPSZNM
    NMZNMNB
    NBNMNMNB
     1) E:偏差,∆E:偏差变化率;P=正,N=负,NB=负大,NM=负中,NS=负小,Z=零中,PS=正小,PM=正中,PB=正大
     1) E: Deviation, ∆E: Change rate of deviation; P=positive, N=negative, NB=negative big, NM=negative medium, NS=negative small, Z=zero medium, PS=positive small, PM=positive medium, PB=positive big
    下载: 导出CSV

    表  4   环境调控设备控制规则

    Table  4   Control rules for environmental control equipment

    模糊控制状态1)
    Fuzzy control
    state
    定量调控等级/%
    Quantitative
    regulation level
    定时调控等级/h
    Timing regulation
    level
    NB00
    NM252
    Z504
    PM756
    PB1008
     1) NB=负大,NM=负中,Z=零中,PM=正中,PB=正大
     1) NB=negative big, NM=negative medium, Z=zero medium, PM=positive medium, PB=positive big
    下载: 导出CSV

    表  5   环境因子对环境调控设备的依赖程度

    Table  5   Dependence degree of environmental factors on environmental control equipment

    设备
    Equipment
    空气温度
    Atmospheric temperature
    土壤温度
    Soil temperature
    土壤湿度
    Soil moisture
    土壤电导率
    Soil electrical conductivity
    水肥一体灌溉机
    Fertigation system
    0.3 0.3 1.0 1.0
    水泵 Water pump 0.3 0.3 1.0 0.8
    灯光 Light 0.5 0.5 0 0
    风机 Fan 0.8 0.8 0.3 0.3
    湿帘 Wet curtain 0.8 0.5 0.3 0
    下载: 导出CSV

    表  6   准确性监测结果1)

    Table  6   Monitoring data of accuracy

    生长时期
    Growth period
    空气温度
    Atmospheric temperature
    土壤温度
    Soil temperature
    土壤湿度
    Soil moisture
    土壤电导率
    Soil electrical conductivity
    系统
    System
    人工
    Artificial
    系统
    System
    人工
    Artificial
    系统
    System
    人工
    Artificial
    系统
    System
    人工
    Artificial
    种子发芽期
    Seed germination period
    190/146 141/195 262/74 224/112 330/6 23/313 263/73 20/316
    叶片生长期
    Leaf growth period
    651/549 445/755 1 023/177 944/278 746/454 185/1 019 808/392 45/1 155
    菜薹形成期
    Stalk formation period
    513/399 252/660 725/187 513/377 811/101 276/632 667/245 37/875
    总计 Total 1 354/1 094 838/1 610 2 010/438 1 681/767 1 887/561 484/1 964 1 738/710 102/2 346
     1)“/”上方为处于适宜范围内的数据量,下方为偏离适宜范围的数据量
     1) The data above “/” are the amount of data in the appropriate range, and the data below “/” are the amount of data that deviate from the appropriate range
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-09-22
  • 网络出版日期:  2023-11-22
  • 发布日期:  2023-08-15
  • 刊出日期:  2024-01-09

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