LED color mixing design based on improved artificial fish swarm algorithm

被引：0

作者：

Luan, Xin-Yuan ^{[1
]}

Liu, Ting-Zhang ^{[1
]}

Zhou, Zhuang-Li ^{[2
]}

机构：

[1] School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Power Station Automation Technology, Shanghai University, Shanghai

[2] Shanghai Liangshuo Photoelectron Co. Ltd., Shanghai

来源：

Faguang Xuebao/Chinese Journal of Luminescence | 2015年 / 36卷 / 01期

关键词：

Artificial fish swarm algorithm; Color mixing; Optimization;

D O I：

10.3788/fgxb20153601.0113

中图分类号：

学科分类号：

摘要：

A novel design of LED mixing color based on improved artificial fish swarm algorithm (AFSA) was proposed. In order to improve convergence rate and accuracy of AFSA, opposition-based reinforcement learning was utilized to optimize solution space of AFSA, Normal and Cauchy distribution function were employed as adaptive weight operators to optimize vision field and step-size. The white, amber and blue LEDs were chosen to design LED lamp samples. LED proportions of 4000 K color temperature among those LEDs were optimized by AFSA and new AFSA in the Matlab. Simulations indicate that improved AFSA has the higher convergence rate and accuracy. After LED lamps were tested by integrating sphere, the results show that the difference between the actual value and simulation calculation value is tiny, and the improved AFSA is effective. The improved AFSA provides a new efficient method for the calculation of LED proportions. Compared with the traditional method, the new method not only saves a significant amount of time, but also achieves higher luminous efficacy for lamps. All these show that the new method is effective and has high practical value. ©, 2014, Chines Academy of Sciences. All right reserved.

引用

页码：113 / 120

页数：7

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