Optimization of a pusher type reheating furnace: An adaptive Model Predictive Control approach

In this paper, an Advanced Process Control system based on a two-layer linear Model Predictive Control strategy is proposed. The control system aims at optimizing a pusher type billets reheating furnace, located in an Italian steel plant. A first principles nonlinear model has been developed, in order to obtain estimations of billets temperature inside the furnace. A Linear Parameter-Varying model for billets temperature has been accordingly derived. To obtain a global modellization of the furnace unit, an additional black-box approach has been adopted for the internal process dynamics. The overall resulting model has been exploited for the design of the Model Predictive Control scheme. Performances on an industrial process have shown the major profitability of the proposed control solution with respect to the previous one, based on a suitable handling of local PID controllers. In particular, significant energy saving has been obtained, together with an improved specifications fulfillment.