科技创新与应用2024，Vol.14Issue(13)：68-72,5.DOI:10.19981/j.CN23-1581/G3.2024.13.017
基于混合人群搜索算法的采煤机调高系统控制研究
摘要
Abstract
In order to improve the control stability of the underground shearer in the coal mine,aiming at the problem of in-sufficient adjustment precision and slow response speed of the shearer in the working process,the Seeker Optimization Algorithm(SOA)is used to adjust its parameters to improve its control effect.At the same time,aiming at the problems existing in the Seeker Optimization Algorithm,such as a large number of individuals gathering in the later stage,unable to make use of effective information,insufficient search speed,and falling into local optimization,this paper presents an improved Seeker Optimization Al-gorithm based on the idea of leader and follower of gray wolf algorithm,Levy flight strategy and chaos mapping strategy to set the parameters of shearer heightening control system.Using the improved Seeker Optimization Algorithm and particle swarm search al-gorithm,using MATLAB simulation and shearer control experiments respectively,comprehensively considering the overshoot,rising time and adjustment time,it is concluded that the convergence speed of the improved SOA algorithm is improved by 2 s,the comprehensive search accuracy is improved,and the adjusted control parameters make the shearer height adjustment system have faster response speed and higher balance.It can provide a certain theoretical basis for efficient mining of shearer in the future.关键词
采煤机/参数整定/人群搜索算法/自动调高/灰狼算法Key words
shearer/parameter setting/Seeker Optimization Algorithm/automatic height adjustment/grey wolf algorithm分类
矿山工程引用本文复制引用
陈智星,王李进,陈鹏飞,徐立新..基于混合人群搜索算法的采煤机调高系统控制研究[J].科技创新与应用,2024,14(13):68-72,5.基金项目
山西省科技厅一般科研课题(202102100401015) （202102100401015）
