An Improved WM Fuzzy Modeling Method for Blast Furnace Gas System
作者单位：School of Control Science and EngineeringDalian University of Technology
会议名称：《第36届中国控制会议》
主办单位：Dalian University of Technology;Systems Engineering Society of China (SESC);Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)
会议日期：2017年
学科分类：080602[工学-钢铁冶金] 08[工学] 0806[工学-冶金工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by the National Natural Sciences Foundation of China(No.61533005,61522304,U1560102) National Sci-Tech Support Plan(No.2015BAF22B01) Fundamental Research Funds for the Central Universities(DUT16RC(3)031) Key Research Projects Funds of Chinese Society of Academic Degrees and Graduate Education
关 键 词：Wang-Mendel fuzzy model simplex unscented kalman filter rules extraction blast furnace gas system
摘 要：The blast furnace gas is an important secondary energy for the iron and steel *** an effective model to describe the state of BFG system is of great significant to maintain the system balance and *** the strong coupling characteristics of the blast furnace gas system and the high level noises in the industrial data,a simplex unscented kalman filter-based Wang-Mendel modeling method is proposed in this paper to improve the accuracy and generalization ability of the fuzzy *** the proposed method,the maximum posterior estimation of the center value in each fuzzy rule space is calculated in the probability density distribution perspectives by incorporating the kalman filtering method into rule extraction process,which eliminates the influence of noises effectively and improves the accuracy of the fuzzy *** experimental results by using the Lorenz time series with noises and the industrial data demonstrated that the proposed method could extract the fuzzy rules from the data accurately and had good performance for blast furnace gas system modeling.