基于遗传算法优化的云模型PID液压弯辊板形控制  

Hydraulic bending roll flatness control of cloud model PID based on genetic alogorithm optimization

作　　者：白涛[1] BAI Tao(Department of Student Affairs,Chengde Petroleum College,Chengde 067000,China)

机构地区：[1]承德石油高等专科学校学生工作部,河北承德067000

出　　处：《塑性工程学报》2021年第4期206-211,共6页Journal of Plasticity Engineering

摘　　要：为实现液压弯辊板形控制系统的精确控制,设计了一种基于遗传算法优化的云模型PID控制器,该算法将云模型处理不确定性问题的优势和PID控制的良好稳定性相结合,并且运用遗传算法全局优化能力对云模型PID控制器的数字特征进行了优化,进一步改进了云模型PID控制器的控制效果。以某公司1220 mm液压弯辊板形控制系统作为仿真对象进行了仿真,结果表明,基于遗传算法优化的云模型PID控制对提高液压系统的油压动态响应速度和稳态跟踪精度十分有效,其控制效果优于无优化的云模型PID控制以及传统PID控制。To realize the precise control of hydraulic bending roll flatness control system,a cloud model PID controller based on genetic algorithm optimization was designed. The algorithm combines the advantages of cloud model in dealing with uncertainty problems and the good stability of PID control,and the global optimization ability of genetic algorithm was used to optimize the digital characteristics of cloud model PID controller. The control effect of cloud model PID controller is further improved. The simulation of 1220 mm hydraulic bending roll flatness control system of a company was carried out. The results show that the cloud model PID control based on genetic algorithm optimization is very effective to improve the dynamic response speed and steady-state tracking accuracy of hydraulic system,and its control effect is better than that of the cloud model PID control without optimization and the traditional PID control.

关 键 词：液压弯辊 板形控制 遗传算法 云模型 PID控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]