摘要
针对离心选矿系统强耦合、非线性等问题,提出一种基于自适应粒子群优化(APSO)算法优化模糊解耦比例-积分-微分(PID)控制器的智能方法。先利用模糊解耦算法设计模糊PID控制器,实现给矿流量和给矿质量分数分别由给水量和固体给料量直接控制,再引入APSO算法对模糊PID控制器的参数进行动态优化。仿真与实验结果表明:该方法具有响应速度快、超调量小等特点,且选矿机铁精矿富集比有显著提高。
Aiming at the problems of strong coupling and nonlinearity of the centrifuge separation system,an intelligent method based on adaptive particle swarm optimization(APSO)algorithm to optimize fuzzy decoupling proportion integration differentiation(PID)controller is proposed.Firstly,fuzzy decoupling algorithm is used to design the fuzzy PID controller,which realizes the direct control of the feed flow and the quality of the feed by the feed water quantity and solid feed quantity respectively,and then introduces the APSO algorithm to dynamically optimize the parameters of the fuzzy PID controller.Simulation and experimental results show that the method has the characteristics of fast response speed,small overshoot,etc.and the concentration ratio of iron concentrate of the concentrator is significantly improved.
作者
罗小燕
吴庆龄
倪俊
刘鑫
LUO Xiaoyan;WU Qingling;NI Jun;LIU Xin(School of Mechanical and Electrical Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China;Jiangxi Mechanical and Electrical Equipment Tendering Co Ltd,Ganzhou 341000,China)
出处
《传感器与微系统》
CSCD
北大核心
2022年第6期103-105,113,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(51464017)
江西省重点研发计划资助项目(20181ACE50034)。
关键词
离心选矿
模糊解耦比例-积分-微分控制
自适应粒子群优化算法
模糊比例-积分-微分控制器
centrifuge separation
fuzzy decoupling proportion integration differentiation(PID)control
adaptive particle swarm optimizational(APSO)algorithm
fuzzy PID controller
