@article{WAN2023, 
author = {Chunqiu WAN and Qing LI and Jiarui CUI and Xisheng LI and Yinmei XU},
title = {The intelligent parameter optimization and experimental design for finish rolling AGC system based on PSO},
year = {2023},
journal = {Experimental Technology and Management},
volume = {40},
number = {5},
pages = {31-37,99},
keywords = {particle swarm optimization (PSO) algorithm, finish rolling AGC system, PSO-PI intelligent optimal control, weighted coefficient method, virtual simulation experimental system},
url = {https://www.sciopen.com/article/10.16791/j.cnki.sjg.2023.05.005},
doi = {10.16791/j.cnki.sjg.2023.05.005},
abstract = {The classical particle swarm optimization (PSO) algorithm and four PSO algorithms with different improved forms are employed to optimize the PI control parameters of the automatic gauge control (AGC) of the finish rolling system. In this way, an intelligent optimal control system for finish rolling AGC based on PSO-PI control strategy is constructed. In the process of control parameters tuning, the optimization problem of multiple performance indicators, such as control accuracy and dynamic response characteristics, is transformed into a single objective optimization problem through the weighted coefficient method, and the influence of the weight coefficient of each control indicator on the control effect is studied through simulation experiments. Finally, based on the research results of PSO algorithm, an intelligent optimal control virtual simulation experimental system for finish rolling AGC is constructed. And it provides strong support for students to cultivate their ability to solve complex engineering problems in the field of metallurgical automation.}
}