ANFIS在光电检测中的应用研究  

The Application of Adaptive Neuro-fuzzy Inference System in Photoelectric Detection

作　　者：王立刚[1] 建天成[1] 肖翠红[1] 

机构地区：[1]东北石油大学电子科学学院,大庆163311

出　　处：《科学技术与工程》2010年第26期6445-6448,共4页Science Technology and Engineering

摘　　要：光电检测系统会受到各种噪声和环境温度变化的影响而产生一定的误差,因此只有进行误差补偿才能够提高检测精度。为更好地实现误差补偿功能,建立了基于光电检测的自适应神经模糊推理系统(ANFIS),这种Takagi-Sugeno模型的推理系统能够自动调整隶属函数参数和自动生成模糊规则,克服了模糊控制系统缺乏在线自学习能力或自调整能力的缺点,仿真结果表明这种推理系统模型适用于光电检测并能够提高光电检测的检测精度。Photoelectric detection system will be affected by various noises and variational environmental temperature and produce a certain error,only to error compensation can improve detection accuracy.For realizing better error compensation function. The photoelectric detection system is established which based on Adaptive Neuro-Fuzzy Inference System. This kind of Takagi-Sugeno model of Adaptive Neuro-Fuzzy Inference System can automatically adjust membership function parameters and adjust the fuzzy rules.This model has overcomed the shortcomings of the fuzzy control system which lack of on-line self-learning ability and self-adjusting capability. Simulation results show that this inference system model applies to photoelectric detection system and can improve the precision of photoelectric detection.

关 键 词：模糊技术 模糊神经 光电检测 ANFIS 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]