文献类型：期刊文献

英文题名：Air-fuel-ratio optimal control of a gas heating furnace based oil fuzzy neural networks

作者：Cao, Heng[1]; Du, Ding[1]; Peng, Yunhua[2]; Yin, Yuhai[1]

机构：[1] School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China; [2] Shanghai Baosteel Chemical Co. Ltd., Shanghai, China

年份：2006

卷号：3973 LNCS

起止页码：876

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20062910011084)

语种：英文

外文关键词：Algorithms - Backpropagation - Fuzzy sets - Gas heating - Neural networks - Optimal control systems - Reliability

摘要：Based on Neural Network BP algorithm and self-optimizing control, taking gas heating furnace air-fuel-ratio optimized control as goal, a new heating furnace intelligent control algorithm is raised and applied in the practice. Comparing fuzzy neural network hybrid algorithm and PID control algorithm, with gas heating furnace energy-saving control reconstruct, new algorithm can achieve function of automatic tracking calorific value variable and adjusting air-fuel-ratio. The characteristics of this algorithm are high precision and reliability, and suitable for project application. ? Springer-Verlag Berlin Heidelberg 2006.