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

    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.

       

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