臺灣博碩士論文加值系統

本論文中，利用實數型基因演算法 (Real-coded Genetic Algorithm, RGA) 對於植物生長燈系統做最佳化設計，並且由過去文獻我們得知植物生長可被以下各參數所影響: 波長、頻率、工作比以及光強度等等。因此，本論文設計光源刺激系統透過人機界面 (LabVIEW) 能彈性的調整這些參數。在本文裡，應用多波長 LED 調變後再同步的技術，透過個人電腦、微處理器以及相關介面電路，此系統允許光波長、頻率 (0 ~ 10 kHz)、工作比 (0 ~ 100%)、光強度與相移比 (0 ~ 360o) 可獨立調整的功能。該植物生長燈最佳化設計於照射距離與電流，藉由實數型基因演算法 (RGA) 可有效的改善光均勻度及照明效率。本文應用多目標最佳化，是一種特別針對於多種目標問題的基因演算法 (GA)，與傳統的基因演算法 (GA)計算不同的適應函數，它更能保持解的差異性，藉由此多目標最佳化 (MOGA) 可尋找控制紅藍綠 LED 的輸入電壓與照射距離所得之最佳化照度以及均勻度。

In this paper, a real-coded genetic algorithm (RGA) technique is developed for the optimal design of a supplemental lighting system for plant-growth, which is affected by the parameters: wavelength, frequency, duty ratio and amplitude. A light intensity stimulation system of functional is designed that can provide a flexible interface to adjust the parameters for users and researchers. Here, the technique of modulation and synchronizing in multi-wavelength light emitting diodes (LEDs) are employed. Through operations of the personal computer, microprocessor and related interface circuits, the system allows the light quality, light intensity, frequency (0 ~ 10 kHz), duty ratio (0 ~ 100%) and phase shift (0 ~ 360o) to be controlled. The optimal design in height and current of the plant-growth lamp by the RGA shows the improvement in the light uniformity and illumination efficiency. The innovatively designed systems are compared favorably with the typical and expert-designed lighting systems. It is concluded that the system is satisfactorily suitable to the photosynthesis applications. In multi-objective optimization, a describing genetic algorithm (GA) specifically developed for problems with multiple objectives. Control the input voltage distance of the RGB LEDs, the optimal illumination and uniformity can be found with by multi-objective genetic algorithms (MOGA). They primarily differ from traditional GA by using specialized fitness functions and introducing methods to promote solution diversity.

摘要-------------------------------------------------------i
Abstract--------------------------------------------------ii
Contents--------------------------------------------------iv
Figure caption--------------------------------------------vi
Table caption--------------------------------------------vii
Nomenclature--------------------------------------------viii
Chapter 1 Introduction-------------------------------------1
Chapter 2 Problem formulation------------------------------5
2.1 Source model-------------------------------------------5
2.2 Light uniformity---------------------------------------6
2.3 The design of the plant-growth lamp--------------------6
Chapter 3 Optimization process-----------------------------8
3.1 Multi-objective genetic algorithm (Weighted-sum Method)----------------------------------------------------8
3.2 Multi-objective genetic algorithm (Rank-Based Fitness Assignment Method)-----------------------------------------9
3.3 Optimal lamp placement--------------------------------11
3.3.1 Single-objective optimization problems--------------11
3.3.2 Multi-objective optimization problems---------------12
Chapter 4 Light Control System----------------------------16
4.1 LED lighting panel module-----------------------------16
4.2 Multi-channel modulation signal generators------------16
4.3 System architecture and integration-------------------18
Chapter 5 Numerical Simulations and Experimental Results---------------------------------------------------19
5.1 Numerical simulations---------------------------------19
5.2 Experimental results----------------------------------20
Chapter 6 Conclusions-------------------------------------22
References------------------------------------------------23

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