[1]陈家煜,刘丽桑,张友渊,等.基于改进PID算法的钢铁行车系统建模与控制[J].福建理工大学学报,2024,22(01):47-53.[doi:10.3969/j.issn.2097-3853.2024.01.007]
　CHEN Jiayu,LIU Lisang,ZHANG Youyuan,et al.Modeling and controlling of iron and steel crane system based on improved PID algorithm[J].Journal of Fujian University of Technology;,2024,22(01):47-53.[doi:10.3969/j.issn.2097-3853.2024.01.007]
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基于改进PID算法的钢铁行车系统建模与控制
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《福建理工大学学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第22卷
期数:
2024年01期
页码:
47-53
栏目:
出版日期:
2024-02-25

文章信息/Info

Title:
Modeling and controlling of iron and steel crane system based on improved PID algorithm
作者:
陈家煜; 刘丽桑; 张友渊; 陈炯晖; 王晨曦
福建理工大学电子电气与物理学院
Author(s):
CHEN Jiayu;  LIU Lisang; ZHANG Youyuan; CHEN Jionghui; WANG Chenxi
School of Electronics, Electrical Engineering and Physics, Fujian University of Technology
关键词:
行车; 拉格朗日方程; 动力学建模; PID控制; 仿真实验平台
Keywords:
crane;  Lagrange equation;  dynamics modeling;  PID control;  simulation experiment platform
分类号:
TP273
DOI:
10.3969/j.issn.2097-3853.2024.01.007
文献标志码:
A
摘要:
行车是钢铁物流过程中最重要的设备之一,其运行的稳定性、安全性至关重要。综合考虑了负载摆动对行车系统的影响,利用拉格朗日方程对钢铁物流行车系统进行动力学建模,分析了系统动能和广泛力,并搭建了滑轨行车仿真实验平台。针对传统比例积分微分(PID) 控制器在不确定、非线性系统中控制性能不理想的问题,采用模糊PID 和误差反向传播( BP) 神经网络自适应调整控制器参数,提高了系统的动态性和抗干扰性。将两种改进的智能PID 控制算法与传统PID 进行了仿真实验对比。结果表明,采用BP 神经网络优化的PID 控制器(BP?PID)和模糊PID 性能均优于传统PID,且BP?PID 的响应速度更快、鲁棒性更强。
Abstract:
The crane is one of the most important equipment in the process of iron and steel logistics, and its operational stability and safety are crucial. Considering the impact of load swing on the driving system, the Lagrange’s equation was used to model the dynamics of the steel logistics driving system, the kinetic energy and the extensive force of the system were analyzed, and the simulation experiment platform of the slide rail driving was built. In response to the problem of poor control performance of traditional PID controllers in uncertain and nonlinear systems, fuzzy PID and BP neural networks were used to adaptively adjust controller parameters, improving the dynamic and anti-interference performance of the system. Finally, simulation experiments were conducted to compare the two improved intelligent PID control algorithms with traditional PID. Results show that both BP-PID and fuzzy PID have better performance than traditional PID, and BP-PID has the fastest response speed and robustness.

参考文献/References:

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更新日期/Last Update: 2024-02-25