基于双模糊控制器的城市智慧照明系统  

Urban intelligent lighting system based on dual fuzzy controllers

作　　者：陆万荣 许江淳[1] 曾德斌 杨杰超 LU Wan-rong;XU Jiang-chun;ZENG De-bin(Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China)

机构地区：[1]昆明理工大学信息工程与自动化学院

出　　处：《能源工程》2019年第4期89-94,共6页Energy Engineering

摘　　要：针对城市路灯照明系统存在电能消耗高、调控方案单一等问题,设计了一种基于光照和车流量双模糊控制器的智能照明系统,使用光照度和光照变化率作为光照模糊控制器的输入,车流量检测值和变化率作为车流量模糊控制器的输入。照度数据使用技术成熟且广泛使用的TSL256X光照传感器采集;车流量检测时针对视觉背影提取(visual background extractor,ViBe)算法有漏检静止目标问题,采用改进的ViBe算法;通过指数平滑(exponential smoothing,ES)和径向基函数(radical basis function,RBF)神经网络双模融合的方式得到车流量预测值。结果表明:智能照明系统节能效果理想,系统平均节能达到28.5%。该照明系统增强了天气异常情况应对能力,降低了能源浪费率,提高了路灯照明系统智能化水平。Aiming at the problem of high power consumption and single control scheme for urban street lighting systems, an intelligent lighting system based on dual fuzzy controllers for light and vehicle flow was designed. Illuminance and illuminance change rate were used as input of the light fuzzy controller. Traffic flow detection value and rate change were used as input of the vehicle flow fuzzy controller. Illumination data was collected using the TSL256 X light sensor with a mature and widely used technology. Because visual background extractor algorithm for vehicle flow detection had the problem of missed detection of stationary targets, so an improved ViBe algorithm was adopted.Exponential smoothing and radial basis function neural network dual-mode fusion method was used to obtain the traffic flow prediction value. The result showed that the energy saving effect of the intelligent lighting system was ideal, and the average energy saving of the system reached 28.6%. The lighting system enhanced the ability to respond to abnormal weather conditions, reduced energy wastage, and improved the intelligence level of street lighting systems.

关 键 词：照明系统 双模糊控制器 ViBe算法 RBF神经网络 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]