基于ANFIS高精度光照度计的仿真研究

摘要

为提高光照度计的检测精度,针对光照度检测系统,应用Takagi-Sugeno模型的自适应神经模糊推理方法(ANFIS)到光照度检测系统,对光照度检测电路进行了误差补偿,并给出了硅光电池高精度光照度计的软件仿真.最后利用光照度检测实验平台实测数据作为样本数据,在MATLAB软件下的仿真结果表明:自适应神经模糊推理方法通过自学习,可以调整模糊规则和隶属函数参数,提高了光照度计的检测精度.%To improve the detecting precision of light illuminometer, for the illumination detection system, Takagi-Sugeno model of Adaptive Neural-Fuzzy Inference System( ANFIS) is applied, compensated the error of illumination detection circuits, and introduced software simulation of silicon-photocell high-precision light illuminometer. Finally, using measured data of the light test platform as the sample data, the MATLAB software simulation results show that: Adaptive Neural-Fuzzy Inference System through self-learning , can automatically adjust membership function parameters and the fuzzy rules, improves the precision of illumination detection.