Abstract：The thermal operations of pellet induration have great effects on energy consumption， productivity and pellet quality in grate-kiln process. Due to the process characteristics， such as multiple variables， strong coupling and the complicated relations between manipulated and controlled variables， the thermal process can hardly be effectively controlled by mechanism model. Material flow and thermal airflow of grate-kiln process were firstly analyzed， and then the subtractive clustering based ANFIS (adaptive neural fuzzy inference system) model was proposed to control the thermal state. In this control model， subtractive clustering algorithm was adopted to partition the input data space， while recursive least square method and gradient descent method were used to identify both premise parameters and conclusion parameters of the T-S model. Using a hybrid of VC++ and MATLAB， control system of grate-kiln pellet thermal state was developed， which realizes the online model calculation and the real-time control guidance. Model validation was conducted using the production data of a particular pelletizing plant， and the results show that the mean relative error of the model is less than 5%.
收稿日期: 2015-02-10
出版日期: 2015-10-29
引用本文:
范晓慧，李 曦，陈许玲，杨桂明. 基于减法聚类ANFIS的链-回-环球团热状态控制模型[J]. 钢铁, 2015, 50(11): 21-26.
FAN Xiao-hui，LI Xi，CHEN Xu-ling，YANG Gui-ming. Thermal state control model of grate-kiln pellet based on substractive clustering ANFIS. Iron and Steel, 2015, 50(11): 21-26.
2015, Vol. 50 
