Abstract
Milling is one of the most energy consuming stages of the value production chain in many industries. To minimize the specific energy required, new and more efficient devices and circuits are designed and dedicated optimizing control strategies are applied. This research presents the results of innovative electromagnetic mill energy consumption reduction with dedicated supervisory on-line optimizing control algorithm. The paper describes an algorithm that uses the active power measurement and searches for the minimum on the active constraints of the optimization problem. The constraints follow from the product quality, mill supply voltage and magnetic induction requirements. Algorithm performance was tested in simulations, but the main validation was performed on a semi-industrial dry grinding and classification circuit equipped with an electromagnetic mill. The results of the experiments presented in this paper show that the application of the on-line optimization algorithm allows for even a 40% reduction in the electromagnetic mill energy consumption when compared to the nominal operating point.