基于Elman型回归神经网络的空燃配比优化控制
OPTIMAL CONTROL OF AIR TO FUEL RATIO BASED ON RECURRENT NEURAL NETWORK ABOUT ELMAN
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摘要: 良好的空燃配比是提高燃烧效率、实现最佳燃烧的重要保证．本文针对如何获得最佳空燃配比这一许多企业尚未解决的难题，提出了一种基于Elman型回归神经网络的空燃配比优化控制方案．该方案应用某一加热炉的燃烧控制中，取得了良好的控制效果，具有较高的推广价值．Abstract: Good air to fuel ratio can improve combustion efficiency and achieve optimal combustion.An optimal control strategy based on recurrent neural network about Elman is presented,in which an approach getting an optimal air to fuel ratio is given. Finally, the good control results were obtained when the control scheme was applied to a reheating furnace.It proved to be having higher application value.
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