Design of greenhouse temperature and humidity wireless control system based on CC3200

Referring to the shortages that the process of traditional greenhouse measurement by using thermometer and hygrometer is complex,the measurement result is not accurate,and the control system operation is cumbersome,a greenhouse temperature and humidity(TH)control system based on CC3200 is designed.The system uses FPGA as the main controller,sends the TH signals to the wireless module CC3200 by controlling DHT22.The proposed system realizes the remote transmission of data and the automatic control of system.

Determining heating pipe temperature in greenhouse using proportional integral plus feedforward control and radial basic function neural-networks

Proportional integral plus feedforward (PI+FF) control was proposed for identifying the pipe temperature in hot water heating greenhouse. To get satisfying control result, ten coefficients must be adjusted properly. The data for training and testing the radial basic function (RBF) neural-networks model of greenhouse were collected in a 1028 m2 multi-span glasshouse. Based on this model, a method of coefficients adjustment is described in this article.

Research and Analysis on Cooling Capacity of Temperature Adjustment Equipments in Agricultural Multi-span Greenhouse

The high summer indoor temperature in agricultural greenhouse is not conducive to crop growth,so it is necessary to cool the greenhouse. In this study,taking the agricultural multi-span greenhouse with strong temperature adjustment ability for example,we make an experimental analysis on the temperature changes inside and outside the greenhouse under nine different equipment combinations( fan,skylight,sunshade,sunshade + fan,cooling pad + fan,skylight + fan,sunshade + skylight,sunshade + fan + cooling pad,sunshade + skylight + fan),respectively,and conduct the overall assessment on the measures to cool the summer agricultural greenhouse,in order to provide a reference for selecting a cost-effective cooling method for greenhouse. Tests show that the three treatment modes of fan,sunshade and sunshade + fan almost have no cooling capacity; skylight,sunshade + skylight have cooling capacity,but the effect is slow; cooling pad + fan,sunshade + skylight +fan can reduce the indoor temperature,but the effect is not very good; skylight and fan have good cooling effect; sunshade + fan + cooling pad has obvious cooling effect,which can well meet the cooling needs in the summer greenhouse.

Temperature and Humidity Control in Greenhouses in Desert Areas

Water consumption can be reduced by using a greenhouse for agriculture in desert areas. We analyzed the effect of control of ventilation, sprinkler water, and solar radiation?shielding on changes of temperature and humidity in a greenhouse under various desert area conditions. We calculated the changes in temperature and humidity in a greenhouse for a whole day in four seasons, and the calculation results of water consumption with and without a greenhouse were compared. When ventilation, shielding, and sprinkler water were controlled under suitable conditions to grow orchids in a desert area, water consumption in July was only 7% of that without a greenhouse.

Temperature-Based Fan Speed Optimization Strategy

As energy efficiency and indoor comfort increasingly become key standards in modern residential and office environments,research on intelligent fan speed control systems has become particularly important.This study aims to develop a temperature-feedback-based fan speed optimization strategy to achieve higher energy efficiency and user comfort.Firstly,by analyzing existing fan speed control technologies,their main limitations are identified,such as the inability to achieve smooth speed transitions.To address this issue,a BP-PID speed control algorithm is designed,which dynamically adjusts fan speed based on indoor temperature changes.Experimental validation demonstrates that the designed system can achieve smooth speed transitions compared to traditional fan systems while maintaining stable indoor temperatures.Furthermore,the real-time responsiveness of the system is crucial for enhancing user comfort.Our research not only demonstrates the feasibility of temperature-based fan speed optimization strategies in both theory and practice but also provides valuable insights for energy management in future smart home environments.Ultimately,this research outcome will facilitate the development of smart home systems and have a positive impact on environmental sustainability.

Greenhouse Environmental Control Using Optimized, Modeled and Simulated Fuzzy Logic Controller Technique in MATLAB SIMULINK

The main objective of this study is the control of the agricultural greenhouse in view of the economic interest generated by such an activity. A simulation model is developed, gathering all the external and internal climatic conditions that influence the microclimate of the greenhouse to predict the temporal evolution of the state variables characterizing this microclimate. The fuzzy control is an alternative to the approaches proposed by the automatic for the control of complex systems. The performance objectives of the looped systems and the corresponding actions are summarized in the form of rules of expertise, which are spelled out in plain language. This technique thus makes it possible to dispense with the use of mathematical models which are sometimes difficult to obtain. Our objective is the multivariable strategy synthesis and the fuzzy application to a multivariate system （MIMO ~ such as the agricultural greenhouse.） First, the principles of fuzzy logic and fuzzy control are recalled. The origins of non-Linearitys of the command are explained. One of the practical problems of this technique is the combinatorial explosion of the rule base when the number of variables involved becomes large. A solution to simplify the complexity of the system is presented together with an optimization algorithm to automatically adjust the parameters of the fuzzy controller. The last part is devoted to the synthesis of an optimal control of the greenhouse in order to compare it to the fuzzy control implemented.

Technology issues and prevention strategies on sunlight greenhouse vegetable

Energy-saving solar greenhouse vegetables cultivating is to create and improve microclimate environment with greenhouse in those seasons impossible for open cultivation production and in order to achieve the purpose of harvest in advance or in delay. Since a greenhouse needs huge construction expenses and high production costs, only though the improvement of facility utilization can we obtain better economic benefits. Vegetable germination and seedling stage need a long time for ground, so they need smaller standing area. So we concentrated in a small area of cultivation can not only create a suitable environment easily, nurture strong age seedling, but also can avoid greenhouse waste. Make transplanting to greenhouse after Seedlings breeding can effectively reduce the fertility cycle and substantially increase greenhouse utilization.

基于双传感器的枕式包装机速度自动调节系统

包装机速度调节系统存在进入稳态耗时长、稳态误差大和调节精度低的问题,导致产品破损率高,提出基于双传感器的枕式包装机速度自动调节系统。系统硬件采用温度传感器和位置传感器,结合可编程逻辑控制器(Programmable Logic Controller,PLC)转换和调配各个机构的速度,实现包装机速度自动调节;系统软件采用等时间原则,确定包装盒传输到封端位置和温度的时间,从而匹配速度,根据齿轮传动原理确定速度变化量,实现枕式包装机速度自动调节。实验结果表明,设计系统进入稳态的耗时仅为20 s,包装破损率均低于7.5%,该系统减小了超调量、缩短耗时、提高控制精度,降低了不同尺寸产品包装破损率,具有较好的通用性和可靠性。

基于CFD与TRNSYS的圆形猪舍内环境控制研究

为了给寒冷地区密闭圆形猪舍提供内环境控制策略,试验以地处寒冷地区的张家口市某在建密闭圆形猪舍为研究对象,通过ANSYS FLUENT软件搭建计算流体力学(computational fluid dynamics,CFD)仿真模型,利用CFD模型计算猪舍在最低通风量标准条件下舍内污染气体质量浓度与风速分布,研究通风量对舍内污染气体质量浓度的影响;利用TRNSYS 17软件搭建猪舍温控仿真模型,以月舍温、月舒适时间占比和月暖通不保证率为评价指标,研究非供热策略、供热策略和调整养殖密度策略下猪舍全年通风量对舍内环境温度与舒适性的影响,筛选较为合适的猪舍全年温控策略,并对最适温控策略进行优化研究。结果表明:在圆形猪舍内每60°布置一组送、排风侧立管的“上送侧排”通风方案中,污染气体浓度随通风量增大而降低;在全年最低通风量[0.35 m~3/(h·kg)]标准条件下,养殖区域猪只背部高度平面的平均风速为0.3 m/s,猪只呼吸高度平面NH_(3)、H_(2)S、CO_(2)质量浓度最大值分别为1.02,0.021,525 mg/m~3,上述参数均满足猪舍养殖环境要求,即通风量、污染物浓度、猪只吹风感之间得到较好平衡。调整养殖密度策略比供热策略的全年平均月舒适时间占比高1.5百分点,全年平均月暖通不保证率低0.2百分点;调整养殖密度策略在夏季的平均月舒适时间占比比非供热策略高4.3百分点,月平均舍温低0.3℃,因此育肥猪舍采用调整养殖密度策略调节猪舍温度更为合适。猪舍采用调整养殖密度策略调节猪舍温度时,将5,9月份的通风量从0.50 m~3/(h·kg)提升至0.68 m~3/(h·kg),使这两个月份的月平均舍温均下降2.3℃,月暖通不保证率分别从1.6%和7.2%下降至0.9%和3.6%,月舒适时间占比分别从35.9%和26.1%提升至70.4%和59.4%;夏季采用遮光板辅助降温措施可使午间猪舍温度降低0.3~1.2℃,使猪舍温度更加舒适。说明应用新风全热交换器和湿帘-风机系统并适当调整通风量或养殖密度可以达到密闭圆形猪舍的环境控制要求。

基于模糊PID算法的食用菌大棚温度控制系统研究

食用菌大棚温度控制系统是一个具有时滞性的复杂系统,传统的开关量或常规PID控制很难满足设计要求。该研究设计一种基于STM32F103CRT6单片机为控制核心,加入模糊自适应PID控制算法,利用DHT11温湿度传感器进行温度实时采集,单片机运算处理,光耦固态继电器驱动电路对热风机进行控制,从而达到温度调节的目的。并在MATLAB/simulink环境下建立常规PID控制和模糊自适应PID控制的仿真模型,通过仿真结果,对比验证了该方法比常规PID控制方法具有低超调量和调节时间短等较好的控制效果。

基于主元分析的温室物联网空气温湿度传感器故障诊断

针对温室物联网测控系统中空气温湿度传感器受恶劣环境影响易发生故障的问题,研究温室物联网测控系统中空气温湿度传感器的故障诊断,保障温室物联网测控系统整体工作的稳定可靠性,提出一种基于主元分析的空气温湿度传感器故障诊断方法。首先对空气温湿度传感器数据进行主元分析,通过监控平方预测误差统计量的变化实现传感器的故障检测;再针对检测出的空气温湿度传感器故障数据,利用加权后的平方预测误差统计量来计算传感器的累积贡献率,并将其作为传感器故障识别的指标,识别出现故障的空气温湿度传感器。利用空气温湿度传感器数据在不同故障条件下进行传感器故障诊断方法验证,验证结果表明:所提方法可用于温室物联网测控系统中空气温湿度传感器偏差故障和漂移故障的检测,偏差故障的检测效果要好于漂移故障,偏差故障综合检测率为100%,漂移故障综合检测率为51.25%;同时所提方法能够正确识别出故障传感器,有效提高温室物联网测控系统中空气温湿度传感器故障诊断结果的准确性。

信息物理系统(cyber-physical system)时空建模方法及在温室控制中的应用

传统农业采用人工方式对温室进行控制,但是随着现代农业的快速发展,这种人工投入大、精度低的控制方式已不能满足现代农业需要。该文基于分层有限状态机和事件晶格的概念,建立3层的信息物理系统模型,并提出一种基于分层有限状态机的信息物理系统时空建模方法,同时利用该建模方法开发了新的温室控制系统。该系统能够将物理层传感器感知到的温室物理环境数据通过物理-信息层汇聚节点融合后上报信息层决策节点得到决策信息,物理-信息层控制节点分析决策信息得到控制信息后下传物理层执行器进行控制。由于该系统模型考虑了各层状态机中事件的时空属性,能够将温室控制的正确率由传统基于物联网的温室控制方法的80.20%提高到87.20%,错误肯定率和错误否定率由7.50%和12.30%下降到3.60%和9.20%,保障温室环境满足作物生长对温度、湿度和光照的要求。

基于模糊自适应控制的温室温度调控

为了实现温室在冬季时温度控制精度高、能耗小的目标,该研究提出了一种将热量平衡原理与模糊控制相结合的模糊自适应控制方法,在模糊控制器中加入基于热量平衡方程的输出隶属度函数修正模块,通过监测温室内外温度数据,在上位机中对模糊控制器中的输出隶属度函数进行自适应调整,最终使温室温度稳定在目标温度。结果表明,基于热量平衡方程的温室温度模糊自适应控制系统具有较好的稳定性和准确性,在设置20℃为目标温度值的情况下,基于热量平衡方程的模糊自适应控制最终使温室温度稳定在(19.8±0.11)℃,一般模糊控制方法最终使温室温度稳定在(13.5±0.5)℃,无法达到目标环境温度值,而阈值控制最终使温室温度稳定在(20.0±0.85)℃;同时,基于热量平衡方程的温室温度模糊自适应控制能耗较低,且能量利用率更高,模糊自适应控制能量利用率为45.97%,而阈值能量利用率仅为20.21%。研究提出的基于热量平衡方程的模糊自适应控制方法不仅满足温室温度调控需求,而且能够提高能量利用率,降低能耗。

基于农业电气自动化的大棚智能控温系统设计

为了实现大棚温度的精确控制,基于数据融合与模糊控制技术,设计了智能温控系统。温度数据融合包括异常数据剔除、节点内数据融合与节点间数据融合,最终输出大棚温度表征量。模糊温度控制输入量为大棚温度表征量及其与设置值的偏差量,输出为温度调控设备控制信号。对系统中温度数据融合性能进行测试,结果表明:该方法优于平均值法;对温度控制性能进行测试,结果表明系统介入后温度相对偏差区间为[-2.5%,3.5%]。

基于SO-BP神经网络的温室环境预测模型研究

由于温室环境中温湿度的调控过程存在滞后响应特性,预测温室环境变化趋势是构建温室精准控制系统中不可或缺的一部分。针对传统神经网络算法在温室预测方面精度不足等问题,提出一种基于蛇优化算法(snake optimizer,SO)优化BP神经网络的温室环境预测方法。试验结果表明,该方法预测15 min内温度的决定系数R^(2)为0.9564,比BP模型、HHO-BP模型分别提高14.87%、2.19%,平均绝对误差MAE、平均绝对百分比误差MAPE、均方根误差RMSE值分别为0.4813、2.2378、0.6729;预测15 min内湿度的R^(2)为0.9821,比BP模型、HHO-BP模型分别提高13.12%、2.37%,预测指标MAE、MAPE、RMSE值分别为1.7090、2.5842、2.2838。该模型的预测结果较理想,可用于温室温湿度预测。

设施温室物联网智能测控系统研究

针对温室环境调控中手动控制和阈值条件调控存在调控精度低、参数超调严重等问题,以设施番茄温室为例,研究提出一种基于环境预测的精准调控策略。首先,构建专用物联网“六域”架构,采用MSP430F5438A作为主控模块,设计感知、通信等功能模块。其次,构建SSA-LSTM预测模型实现对温室环境的精准预测,并根据模型预测结果确定环境调控策略,通过PSO-PID控制模型实现对温室风口电机的精准控制。实验结果表明,相较于传统LSTM模型,SSA-LSTM预测模型的MAE降低58.52%,MAPE降低61.68%,RMSE降低63.84%。同时,相较于传统PID模型,PSO-PID控制模型的超调量降低89.99%,调节时间降低59.85%。系统经过实地部署验证,在保持种植品种和农事管理操作一致的情形下,智能调控的温室产量相较于传统温室提升约8.5%,证明了系统的有效实用性。

温室大跨度薄膜风筒送风特性模拟及试验研究

现代大型温室普遍使用送风末端为长距离柔性薄膜风筒的空气处理机组(air handling unit,AHU)作为温度控制功能单元来完成大空间内的热量输送。为探究此类风筒AHU的性能,该研究采用理论分析和数值模拟方法研究其送风特性,并通过试验验证计算模型的正确性。结果显示,薄膜风筒内不同截面的静压在开孔部位急剧减低至0,同时气流速度明显增加,但是影响范围不大,对风筒内的压力场和流场影响较小。在风筒同一截面上不同开孔位置流出的气体速度和速度分布基本一致,以风筒入口端风速2.45 m/s为例,在风筒60.06 m处风筒壁开孔处气流最大速度为5.64 m/s,位于开孔中心处,并垂直与开孔平面向外流动,速度分布为中心流速最高,越靠近孔边缘流速越低。对风筒沿长度方向通过筒壁各开孔流出的风量进行计算发现,在不同风筒入口风速条件下送风量基本保持恒定,均匀性系数均大于0.92,说明此类风筒能够沿长度方向均匀地配送气流,可将热量或者冷量在温室大空间内进行均匀投送,从而为现代大型温室内空间内维持温度场均匀提供保障。

农业大棚温湿度智能控制与应用

以农业大棚作物温湿度需求为研究对象,对土壤含水率、光照强度及农业大棚室内温度进行实时监测,通过灌溉方式、遮阳策略和通风策略保证作物温湿度需求。采用可编程控制器(PLC)建立温湿度控制系统,分区进行土壤的湿度、光照强度及室内温度信息采集,采用上位计算机对数据进行分析处理,按照控制程序生成指令;也可以通过上位机查看农业大棚温湿度情况,同时通过自动或手动调节农业大棚温湿度。经试验验证,该系统有较高的可靠性,可以在农业大棚中广泛应用。

基于LoRa无线传感网络的农业温室大棚环境测控系统设计

温室大棚是种植反季农作物的重要设施,棚内环境参数直接决定了农作物的生产质量和数量;然而,现有的测控系统由于受天气条件等因素的影响,导致环境温湿度测试存在一定的误差;为了满足农作物的生长需求,并提高精确度,提出了基于LoRa无线传感网络的农业温室大棚环境测控系统的优化设计;通过改装传感器设备和调整数据处理器和控制器的内部结构,构建了系统数据库并组建了LoRa无线传感网络,实现了实时采集大棚环境数据和传输到系统终端;通过计算调整控制量,实现了对农业温室大棚环境的测控功能;实验结果显示,与传统测控系统相比,优化设计的系统在环境温湿度测试方面的误差显著降低了,分别降低了3.65℃和3.75%。

基于模糊PID控制的大棚温控系统设计

随着我国农业的发展,人们对反季节作物的需求越来越高,大棚产业逐渐发展成熟.文章建立了基于模糊PID控制的大棚温控系统,分析了大棚中温度在调控器作用下的变化情况,给出了其数学模型,描述了模糊PID控制的原理,设计了基于模糊PID控制的大棚温控系统,并在Simulink中搭建了仿真模型.仿真结果显示,基于模糊PID控制的大棚温控系统可快速、有效地调控大棚中的温度.与传统PID控制相比,该系统控制效果更好,可大幅缩短控制时间.