磨矿分级过程模糊控制研究与仿真  

Research and Simulation of Fuzzy Control on Grinding and Classification Process

作　　者：于云鹏[1] 王岩[1] 

机构地区：[1]哈尔滨工业大学控制科学与工程系,黑龙江哈尔滨150001

出　　处：《金属矿山》2017年第1期149-153,共5页Metal Mine

摘　　要：选矿厂的磨矿分级系统具有大惯性、纯时滞长、非线性强及时变性等特点,应用传统自动控制方法较难使磨矿分级产品达到工艺要求。针对此问题,哈尔滨工业大学相关课题组提出了不依赖控制对象数学模型,仅使用生产数据进行建模的一阶TSK(Tagaki-Sugeno-Kang)模糊控制方法。该方法通过专家经验分析磨矿分级过程中各变量的耦合及影响关系,确定磨矿过程中需要控制的控制量,再利用大量的测量数据计算得到模糊规则库,规则库对论域范围内的输入值进行计算,并得到模糊输出值,即模糊控制器。此方法可以通过修改模糊规则数量来改变控制精度,实现对磨矿分级过程的高效控制。The grinding and classification process system of the concentrator has the characteristics of large inertia,long time lag, strongly nonlinear and time variation. The traditional automatic control method is hard to make the grinding and grad- ing products meet the technological requirements. To solve this problem, the research group from Harbin Institute of Technology proposes a first-order TSK （Tagaki-Sugeno-Kang） fuzzy control method which does not rely on the accurate mathematical mod- el and only uses the production data to model. This method analyzes the coupling and relationship of the variables in the process of grinding and classification by expert experience. Then the number of variables needed to control is determined, and a large number of measurement data are adopted to obtain fuzzy rule base. The rule base calculates the input values within the domain of the universe and the fuzzy output value is obtained, called the final fuzzy controller. The method can change the pre- cision by modifying the number of fuzzy rules and realize the efficient control of the grinding and classification process.

关 键 词：磨矿 分级 Takagi-Sugeno-Kang模型 模糊控制 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]