High-Performance Automated Optimal Extremal Control of a Material Crushing Process

The study is aimed at maintaining maximum capacity of closed-cycle crushing units using the automated control system by an optimizing extremal control method. This method is based on an optimized parameter extremum search that stores maximum increment and stops the search in the vicinity of maximum capacity. A specific feature of a purpose to be achieved is building an automated control system for crushing raw materials, which are non-homogeneous in their density and composition, to maintain maximum possible capacity of grinding machines. A copper-zinc ore grinding process at one of the Ural deposits in the Russian Federation is used as an example of the proposed improved control method. The authors proposed a new structure of the automated process control system for the copper-zinc ore crushing process in the ball mill that contains memory units to store the extremum of the change in the capacity of the crushing machine. A software-based optimizing extremal search for the grinding process eliminates a search periodic operation mode of the automated control system and reduces by twice testing control actions in a limiting finite state of the optimized process. The search optimizing extremal control of the bulk material grinding process focuses on software-based control and does not entail considerable expense for its introduction, while increasing reliability of feedstock dosing units. The mathematical simulation proved that the most appropriate change in the feeding rate within one step was 2 $\div$ 2.5 t/h ensuring appropriate losses for an extremum search.