基于自适应极限学习机的磨机负荷智能控制研究
投稿时间:2020-03-24  修订日期:2020-06-20  点此下载全文
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徐岳清 无锡机电高等职业技术学校江苏无锡 无锡汽车工程高等职业技术学校江苏无锡 xuyueqing2020@163.com 
陈旗 无锡机电高等职业技术学校  
中文摘要:磨机在运行过程中具有非线性、大惯性、随机干扰大等特征,采用常规PID方法控制负荷存在一定程度的不适应性,针对此问题本文提出了基于自适应极限学习机的磨机负荷智能控制方法。通过对磨机运行工艺和运行特性进行分析,设计了磨机磨矿过程的控制策略思路,利用自适应极限学习机构建了磨机控制系统模型,结合黄金分割法寻找磨机最佳负荷,保证磨机在稳定负荷下运行。应用效果表明,该控制方法能够有效的消除扰动对磨机负荷的影响,主动寻找磨机最佳负荷使得磨机稳定运行,具有较好的自适应能力,对提高磨矿效率和改善分级效果具有一定的意义。
中文关键词:极限学习机  磨机负荷  黄金分割法  智能控制  磨矿
 
Research on Intelligent Control of Mill Load Based on Adaptive Limit Learning Machine
Abstract:Absrtact: The mill has the characteristics of non-linearity, large inertia and large random disturbance during operation, which makes the conventional PID method unsuitable for load control to a certain extent. In order to solve this problem, an intelligent control method of mill load based on adaptive limit learning machine is proposed. Based on the analysis of the operation process and characteristics of the mill, the design idea of the control strategy for the grinding process of the mill is put forward. The control system model of the mill is built by using the adaptive limit learning mechanism. The optimal load of the mill is found by combining the golden section method to ensure that the mill runs under the stable load. The application results show that the control method can effectively eliminate the influence of disturbance on mill load. Actively searching for the optimum load of the mill makes the mill run steadily. It has good adaptive ability. It has certain significance for improving grinding efficiency and classification effect.
keywords:extreme learning machine  mill load  golden section method  intelligent control  grinding
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