Run-of-mine ore is usually too large to be useful for construction or metallurgy. Large particles must be reduced to specific sizes to either comply with aggregate sizing regulations, or facilitate mineral liberation; therefore, in the aggregates and mineral processing industries, run-of-mine ore is broken in crushing circuits by cone crushers. Here, we review the cone crusher literature, focusing on the modeling and control of crushing circuits. A total of 61 works published in the primary literature, ranging from 1972 to 2020, are classified and discussed with respect to the model formulation—i.e., population balance models, empirical models, or data-driven models—and control strategy—i.e., proportional-integral-derivative, model predictive control, expert system, or model-free control. The data are summarized in a table that makes locating a particular formulation or strategy quick and easy. The discussion of the current state of the art of crushing circuit modeling and control technologies consolidates the results available in the literature, as well as the challenges that we must overcome to increase crushing performance through control and optimization. The discussion of future trends brings attention to the discrete element method, model based control, plant-wide and mine-to-mill optimization, and machine learning applications for data acquisition and process optimization.

原矿通常太大而不能用于建筑或冶金。大颗粒必须减少到特定尺寸，以符合骨料尺寸规定，或促进矿物释放；因此，在骨料和矿物加工业中，原矿在破碎回路中由圆锥破碎机破碎。在这里，我们回顾了圆锥破碎机的文献，重点介绍了破碎回路的建模和控制。从 1972 年到 2020 年，在主要文献中发表的总共 61 篇作品，就模型制定（即人口平衡模型、经验模型或数据驱动模型）和控制策略（即比例模型）进行了分类和讨论。 - 积分微分、模型预测控制、专家系统或无模型控制。数据汇总在一个表格中，可以快速轻松地找到特定的配方或策略。对破碎回路建模和控制技术的当前状态的讨论巩固了文献中的可用结果，以及我们必须克服的挑战，以通过控制和优化来提高破碎性能。对未来趋势的讨论将注意力集中在离散元方法、基于模型的控制、工厂范围和矿山到工厂优化以及用于数据采集和过程优化的机器学习应用。以及我们必须克服的挑战，以通过控制和优化来提高破碎性能。对未来趋势的讨论将注意力集中在离散元方法、基于模型的控制、工厂范围和矿山到工厂优化以及用于数据采集和过程优化的机器学习应用。以及我们必须克服的挑战，以通过控制和优化来提高破碎性能。对未来趋势的讨论将注意力集中在离散元方法、基于模型的控制、工厂范围和矿山到工厂优化以及用于数据采集和过程优化的机器学习应用。