摘要
随着矿物加工行业向智能化与高效化转型,模糊控制技术凭借其对非线性、多变量及不确定性系统的优越处理能力,成为该领域技术升级的核心研究方向。为了掌握模糊控制技术在矿物加工行业的应用研究进展,重点分析了其在磨矿分级、浮选、重介分选等关键工艺中的实践成效。研究表明,多变量模糊控制系统通过解耦建模、“双输入单输出”设计及模糊神经网络等方法,有效缓解了变量间耦合问题;与神经网络的结合(如模糊“前馈-反馈”策略、模糊神经网络控制器)显著提升了控制精度与鲁棒性;复合控制技术(如模糊PID、PLC集成)则优化了系统的自适应性,解决了传统工业控制参数固化、滞后性强等瓶颈。此外,智能算法(如加权WM算法、案例推理结合RBF网络)在模糊规则提取中的应用,以及变论域控制、滑动窗口、APSO算法等技术对系统稳定性的改进,进一步加强了模糊控制的工程适用性。未来,模糊控制系统将与浮选、重选、磁选等矿物加工过程全流程协同,助力矿物加工行业的智能化、高效化发展。
As the mineral processing industry transitions towards intelligence and efficiency,fuzzy control technology has become a core research direction for technological advancement in this field due to its superior ability to handle nonlinear,multivariate,and uncertain systems.To understand the research progress in the application of fuzzy control technology in the mineral processing industry,we focus on analyzing its practical effectiveness in key processes such as grinding and classification,flotation,and dense medium separation.Research shows that multivariate fuzzy control systems effectively alleviate coupling issues between variables through methods such as decoupling modeling,“dual-input single-output”design,and fuzzy neural networks.The integration with neural networks(e.g.,fuzzy“feedforward-feedback”strategies,fuzzy neural network controllers)significantly improves control accuracy and robustness.Composite control technologies(e.g.,fuzzy PID,PLC integration)optimize system adaptability,addressing bottlenecks such as fixed parameters and strong hysteresis in traditional industrial control.Furthermore,the application of intelligent algorithms(e.g.,weighted WM algorithm,case-based reasoning combined with RBF networks)in fuzzy rule extraction,as well as improvements in system stability through techniques such as variable universe control,sliding windows,and APSO algorithms,further enhance the engineering applicability of fuzzy control.In the future,fuzzy control systems will be fully integrated with the entire mineral processing workflow,including flotation,gravity separation,and magnetic separation,assisting the intelligent and high-efficiency development of the mineral processing industry.
作者
陈岩
孙玉金
董宪姝
弓佩文
CHEN Yan;SUN Yujin;DONG Xianshu;GONG Peiwen(College of Mining Engineering,Taiyuan University of Technology,Taiyuan 030024,China)
出处
《煤炭工程》
北大核心
2026年第1期200-207,共8页
Coal Engineering
基金
国家重点研发计划项目“难选焦煤精深分选关键工艺环节的精准控制技术”(2023YFC2907705)。
关键词
矿物加工智能化
模糊控制
神经网络
模糊规则
多变量模糊控制系统
intelligent mineral processing
fuzzy control
neural networks
fuzzy rules
multivariate fuzzy control system
