基于雷达观测数据的高炉料面多模型控制-控制理论与应用.PDFVIP

29 10 Vol. 29 No. 10 2012 10 Control Theory Applications Oct. 2012 : 1000−8152(2012)10−1277−07 , , , (; , 100083) : , , . c, ; , , , . , , , . , , . 2500 m3 , , . : ; ; ; : TP273 : A Multi-model control of blast furnace burden surface based on observed data of radars LIU De-xin, LI Xiao-li, DING Da-wei, CHEN Xian-zhong (School of Automation and Electrical Engineering; Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education), University of Science and Technology Beijing, Beijing 100083, China) Abstract: The operation of blast furnace is directly affected by the charging distribution. Productivity can be boosted considerably if good charging distribution strategy is adopted. At the same time, great economic benefits will be brought about. In our method, a large amount of burden surface data from radars are classified by using fuzzy c-means clustering, and the multiple models set of burden surface is built. When the expected burden surface is given, multiple control strategies are designed based on multiple burden surfaces of the model set, and multiple charge distribution are obtained. In every charging distribution period, the real time burden surface data will be matched with the model set by fuzzy recognition, and the corresponding charge distribution matrices will be selected for charge distribution until the expected burden surface is produced. Feedback mechanism is formed from the observed data of radars, and closed-loop control is realized. The proposed control strategy is applied to a 2500 m3 blast furnace in an Iron and Steel Plant; the control effect has been impr