摘要
磨机负荷与生产效率和能源消耗有密切的关系,针对选矿厂球磨机运行过程具有非线性、大滞后和时变性的特点,常规的PID控制难以得到预期的控制效果,因而不能长期运行在最佳的磨机负荷工作状态下。该文提出了自寻优算法与模糊控制相结合的控制策略,自寻优算法来实现磨机负荷最佳工作点的动态寻优,同时引入遗传算法来优化模糊控制器的控制规则和隶属度函数,使模糊控制器具有自学习的能力,实现磨机负荷的实时控制,保证磨机安全、稳定运行。实际的仿真结果表明,该控制策略提高了磨机的产量,同时减少了操作人员的劳动强度,实现了磨机安全稳定运行和节能降耗的目标。
Mill load and production efficiency and energy consumption were closely related,according to the characteristics of ball process with nonlinear,larger time-delay and time-varying characteristics,conventional PID control was difficult to obtain the expected control effect.,and therefore cannot run for a long time in the best mill load working condition.This paper presents a control strategy of combination of self-optimization algorithm with fuzzy control,the self-optimizing achieve dynamic optimization of mill load optimal operating point.At the same time,genetic algorithm was introduced to optimize control rules and membership function for fuzzy controller,make fuzzy controller has the ability of self-learning,realize the real-time control of the mill load,guarantee the safe,stable operation of the mill.The simulation results show that,the control strategy improves the mill production,reduce the labor intensity of operators,and realize the goal of safe and stable operation of the mill and energy saving.
出处
《自动化与仪表》
北大核心
2013年第10期35-39,共5页
Automation & Instrumentation
关键词
磨机负荷
自寻优
模糊控制
遗传算法
优化设计
mill load
self-optimizing
fuzzy control
genetic algorithm
optimization design
