计算技术与自动化2017，Vol.36Issue(4)：33-36,4.
基于T-S模糊神经网络分解炉燃烧控制系统设计
Optimal Combustion System Design Based on T-S Fuzzy Neural Network Decomposing
李涛 1梁凯 1高若尘 1申琦 1张慧杰 1宜文1
作者信息
- 1. 湖南大学信息科学与工程学院,湖南长沙410082
- 折叠
摘要
Abstract
A new control method based on T-S neural network is proposed to solve the problem that the decomposition of the calciner is nonlinear,large-lag,multi-disturbance and multivariable process,and it is difficult to realize the automatic control of temperature.In order to solve this problem,this paper firstly analyzes the process of cement pre-decomposition and studies the combustion theory,then uses TS fuzzy control theory to determine the number of rules and the membership function of input variables,using neural network self-learning and self-adaptability Fuzzy reasoning.The simulation results show that the controller has a good control effect on the combustion control of the precalciner and has a better effect than the traditional PID controller.In the actual production applications,with good stability and robustness,and save the consumption of coal and reduce environmental pollution.关键词
分解炉/模糊神经网络/T-S模糊/控制Key words
decomposition furnace/neural network/T-S fuzzy/control分类
信息技术与安全科学引用本文复制引用
李涛,梁凯,高若尘,申琦,张慧杰,宜文..基于T-S模糊神经网络分解炉燃烧控制系统设计[J].计算技术与自动化,2017,36(4):33-36,4.
