Slab curvature compensation in a hot rolling mill by means of fuzzy control
In the flat products steel industry, the hot rolling mill transforms the incoming slabs in a thin coil which then can be processed to obtain the final products. Thickness is reduced by pulling the plate between two parallel rolls while moving the upper work roll. The effect of uneven thickness at both sides can produce deviations in the longitudinal direction of the slab, which have to be manually compensated for an human operator. In this paper a multivariable control system and a fuzzy control system are described and compared. Results are illustrated with real data from ACERALIA STEEL CORPORATION.
Modeling and Control of Plate Mill Processes
In this thesis two processes have been modeled and controlled, namely the plate thickness control and the slab temperature control. The classical solution for the thickness control problem can't handle asymmetric hardness variations and the estimation of the controlled output introduces stability problems. A nonlinear multivariable model for the thickness control system is derived. The parameters of the model for the rolling mill are identified using data from The Danish Steel Works Ltd. and the model is used for designing a nonlinear multivariable thickness control algorithm. The algorithm is evaluated using computer simulations and the new controller is able to handle the asymmetric case and gives a more accurate thickness control compared to the existing control system. The new control strategy is also found to be stable. The task of the slab temperature controller is to ensure a high furnace throughput, and a proper heating quality while minimizing the energy consumption. Models for the slab and furnace temperatures are identified using data collected during normal production at The Danish Steel Works Ltd. A new way of obtaining parameters for the existing slab temperature control system is described. Furthermore, a nonlinear controller is designed which it is shown to be is globally asymptotically stable. The performance of the linear and nonlinear controller are compared using computer simulations which show that the performance of the nonlinear controller is superior to the performance of the linear controller. The linear slab temperature controller design has been implemented in the slab temperature control system at The Danish Steel Works Ltd. The experimental results indicate that the new controller parameters have lead to a 10% increase in furnace capacity, with unchanged heating quality. Data from the reheat furnace no. 2 indicate that the energy consumption has not been increased by the adjustments. (Less)
Development of Advanced Furnace Control Algorithm
In the continuous work on improving product quality and reducing energy consumption at The Danish Steel Works Ltd. the importance of optimal furnace operation has been recognised in many different contexts. Therefore a joint project with the Department of Automatic Control at Lund Institute of Technology has been started with the purpose of developing a novel slab temperature control algorithm for the reheat furnace control system. The article describes the results of this work so far by giving a short description of the ideas behind the new algorithm and presenting simulations where the peerformance of the new algorithm is compared to the performance of a conventional PI-controller. The model for the simulations is found from data collected from one of the reheat furnaces on The Danish Steel Works Ltd. The simulations show that the new algorithm is able to reduce the standard deviation from the final temperature with more than 15% compared to the temperature deviation obtained with the PI-control algorithm. (Less)