基于PSO-SVM的矿山装载车钻机模糊自适应控制研究  

Research on Fuzzy Adaptive Control of Mining Loader Drilling Machine Based on PSO-SVM

作　　者：潘云龙 PAN Yun-long(China Coal Construction Group No.49 Engineering Department,Handan 056003,China)

机构地区：[1]中煤建设集团第四十九工程处,河北邯郸056003

出　　处：《工程建设与设计》2024年第20期73-75,共3页Construction & Design for Engineering

摘　　要：针对矿山装载车钻机的钻压控制精度低的问题,设计了模糊比例-积分-微分控制器。同时针对钻进地层的识别问题,引入了支持向量机与粒子群优化算法相结合的方法进行地层识别模型的构建,以实现后续的钻压控制。结果显示,论文构建的岩层判别模型的识别准确率高达95.84%,且控制器的响应速度明显更快,适应性更强。说明论文所提策略在矿山装载车钻机的控制中具有显著优势,有利于钻探作业的效率提升及质量保证。Aiming at the low precision of weight on bit control of mine loading truck drilling rig,a fuzzy proportional-integral-differential controller is designed.At the same time,support vector machine(SVM)and particle swarm optimization(PSO)are introduced to construct the formation identification model to realize the subsequent weight on bit control.The results showed that the recognition accuracy of the rock layer discrimination model constructed in the study was as high as 95.84%,and the response speed of the proposed controller was significantly faster and more adaptable.The strategy proposed by the research institute has significant advantages in the control of mining loader drilling rigs,which is conducive to improving the efficiency and quality assurance of drilling operations.

关 键 词：PSO-SVM 矿山装载车钻机 模糊自适应控制 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]