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Micro-environment Control by Using Fuzzy Theory
|關鍵字:||微環境控制;模糊理論;Arduino微控制器;開關遲滯截止區控制;Micro-environment control;Fuzzy theory;Arduino micro-controller;ON-OFF control with hysteresis dead zone||Project:||農林學報, Volume 66, Issue 1, Page(s) 45-56||摘要:||
近年來由於全球氣候變遷與極端氣候的挑戰，導致全球的氣候異常，各式的天災不斷發生，糧食危機與因應的解決方案，也不斷產生與推陳出新。而植物工廠是近年新興的技術，其生產模式是在室內透過環控系統控制作物生長所需的光照、溫度、濕度及二氧化碳等；然由於植物工廠生產成本高，不易取得到生產利潤，因此本研究藉由LabVIEW結合低成本Arduino微控制器並搭配模糊理論演算法則，針對微環境氣候中溫度與濕度兩個最重要的參數，進行智慧型調節，營造適合植物生長的環境，期待能以更低廉的成本有效達到微環境中溫度、濕度控制的目的。本研究在實驗中選用開關遲滯截止區控制（ON-OFF Control with Hysteresis Dead Zone）及模糊控制（Fuzzy Control）兩種控制法則，進行溫度及溼度輸出響應比較。最後並透過 5 組不同溫濕度控制目標情境進行實測。結果顯示以模糊控制法進行控制，其變異係數（Coefficient of variation, C.V.）皆小於5%，代表本研究所建置3種歸屬函數搭配81條控制規則之模糊控制系統，已成功地實現微環境中溫度及濕度的模糊控制，有效地以低成本控制滿足微環境中溫、濕環境控制的要求。
In recent years, the global climate change and extreme weather result in the abnormal global climate. All kinds of natural disasters occurred occasionally and globally. Food issue becomes a crisis in many areas. Many solutions were also tried simultaneously. The Plant Factory is one of the solutions tried. The Plant Factory is a new concept and technology integrated and realized in recent years. A confined building, with artificial light, controlled temperature, humidity and carbon dioxide needed for crop growth, dominated by environmental control systems is the production model of the plant factory. However, the high set up and operating cost and the less profits of production made the commercialization of the plant factory progress slowly. Therefore, this approach employs the LabVIEW programing, a low-cost Arduino micro-controller and the fuzzy theory algorithm to create an micro-environment control scheme on temperature and humidity, the two most important parameters, and looks forward to achieve the cost-down purpose on the micro-environment temperature and humidity control for the plant factory. In this study, ON-OFF Control with Hysteresis Dead Zone and Fuzzy Control, two control methods were implemented and compared by 5 required scenarios of temperature and humidity output responses. The results show that the coefficients of variation (C.V.) were less than 5% when Fuzzy control method was employed. It also means that this simple and low-cost fuzzy control scheme proposed with 3 membership functions and 81 control rules is always capable of satisfying the micro-environment requirements.
|Appears in Collections:||農林學報 第66卷 第01期|
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