With the transformation of the mineral processing industry towards intelligence and efficiency, fuzzy control technology, by virtue of its superior handling capability of nonlinear, multivariable, and uncertain systems, has emerged as a core research direction for technological upgrading in this domain. This paper systematically reviews the application advancements of fuzzy control technology in the mineral processing industry, with a key analysis of its practical effects in crucial processes such as grinding and classification, flotation, and heavy medium separation. Research indicates that multivariable fuzzy control systems effectively alleviate the coupling problem among variables through methods like decoupling modeling, "double input single output" design, and fuzzy neural networks; the combination with neural networks (such as fuzzy "feedforward-feedback" strategies and fuzzy neural network controllers) significantly enhances control accuracy and robustness; composite control technologies (such as fuzzy PID and PLC integration) optimize the adaptability of the system and address the bottlenecks of traditional industrial control, such as solidified parameters and strong lag. Furthermore, the application of intelligent algorithms (such as weighted WM algorithms and the combination of case-based reasoning and RBF networks) in fuzzy rule extraction, as well as the improvement of system stability through techniques like variable universe control, sliding window, and APSO algorithms, further promote the engineering applicability of fuzzy control. In the future, fuzzy control systems will be coordinated with the entire process of mineral processing, including flotation, gravity separation, and magnetic separation, offering broader application prospects for the intelligent and green development of the mineral processing industry and facilitating the improvement of production efficiency and the reduction of energy consumption.