基于自适应极限学习机的磨机负荷智能控制研究

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。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,实现了磨机负荷的智能优化控制。应用效果表明,该控制方法能够有效地消除扰动对磨机负荷的影响,主动寻找磨机最佳负荷,使磨机保持稳定运行,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。

Research on Intelligent Control of Mill Load Based on Adaptive Limit Learning Machine

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.