摘要
在复杂动态环境下,传统温室控制系统在精准性、响应速度和资源利用效率方面存在不足。因此,研究设计了一种融合物联网技术与改进优化算法的温室智能控制系统。实验表明,窄带物联网技术在500 m范围内的平均数据传输延迟仅为33.27 ms,丢包率不超过0.58%,优于Wi-Fi和ZigBee技术。数据处理模块通过狄克逊准则和贝叶斯加权融合将温度传感器的误差降低至0.5℃以内,平均绝对误差为0.18℃。改进优化算法结合模糊比例-积分-微分控制在50次迭代内将温度稳定至目标值25℃。此外,系统整体验证结果显示,智能控制系统将环境参数波动幅度降低至3.08%,能耗减少28.6%。研究提出的方法不仅显著提升温室环境调控精度和效率,还为智慧农业提供了高效、可靠的解决方案。
In a complex dynamic environment,the traditional greenhouse control system has shortcomings in terms of accuracy,response speed and resource utilization efficiency.Therefore,a greenhouse intelligent control system integrating Internet of Things technology and improved optimization algorithm is designed.Experiments show that the average data transmission delay of narrowband Internet of Things technology in the 500m range is only 33.27ms,and the packet loss rate is not more than 0.58%,which is better than Wi-Fi and ZigBee technology.The data processing module reduces the error of the temperature sensor to less than 0.5°C through Dixon criterion and Bayesian weighted fusion,and the average absolute error is 0.18°C.The improved optimization algorithm combined with fuzzy proportional-integral-differential control stabilizes the temperature to the target value of 25℃in 50 iterations.In addition,the overall verification results of the system show that the intelligent control system reduces the fluctuation of environmental parameters to 3.08%,and energy consumption is reduced by 28.6%.The proposed method not only significantly improves the precision and efficiency of greenhouse environmental control,but also provides an efficient and reliable solution for smart agriculture.
作者
马亚蕾
张怡
马一棉
MA Yalei;ZHANG Yi;MA Yimian(Shaanxi Vocational and Technical College,Xi’an 710000,China)
出处
《自动化与仪器仪表》
2025年第7期113-116,共4页
Automation & Instrumentation
基金
陕西省教育厅2023年度科学研究计划项目《陕西高质量职业教育教材建设的标准体系及实践路径》(23JM013)
中国高校产学研创新基金—腾讯科技创新教育专项课题《基于课证融合的‘1+X’证书一站式在线学习云平台》(2022TX006)。
关键词
温室
智能控制
物联网
优化算法
模糊PID
greenhouse
intelligent control
internet of things
optimization algorithm
fuzzy PID
