Application of PID parameters optimization based on GWO in mould level system

Liu Sitong, Kong Xiangwei, Hao Peifeng, Gao Hezhan
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Abstract

Mold level stability is a very important factor in the continuous casting process. To effectively control the liquid level at the set value, solve the problems of disturbance, nonlinearity, and time-varying in the system, as well as modeling difficulties caused by uncertain factors, and aiming at the shortcomings of conventional PID control, the gray wolf algorithm is introduced. The gray wolf optimization algorithm is used to self-tune the PID parameters, and the objective function is constructed based on the adjustment time and steady-state error of the mold liquid level system. Finally, the simulation and experimental results show that the algorithm optimization proposed in this paper is compared with the particle swarm algorithm, and the step response of the system is smoother. Gray Wolf optimized PID control has a fast response speed, with an adjustment time of 3.87s, which is lower than 13.46s for conventional PID control and 5.58s for the PSO algorithm. It can significantly improve the control accuracy and other performance indicators of the system. It provides a reference for improving the level control of the continuous casting mold.
基于GWO的PID参数优化在模具液位系统中的应用
结晶器液位稳定性是连铸过程中一个非常重要的因素。为了有效地将液位控制在设定值上,解决系统的扰动、非线性、时变问题,以及不确定因素带来的建模困难,针对传统PID控制的不足,引入了灰狼算法。采用灰狼优化算法对PID参数进行自整定,并根据结晶器液位系统的调整时间和稳态误差构造目标函数。最后,仿真和实验结果表明,本文提出的优化算法与粒子群算法进行了比较,系统的阶跃响应更加平滑。灰狼优化PID控制响应速度快,调整时间为3.87s,低于常规PID控制的13.46s和粒子群算法的5.58s。可以显著提高系统的控制精度和其他性能指标。为提高连铸结晶器的液位控制提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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