Optimization of a simulated iron-oxide pellets induration furnace

Induration furnaces for iron-oxide pellets are expensive processes, due to their high energy consumption. Moreover, they are highly interactive and then complex to control. Real-time optimization strategies based on reliable process models are thus necessary. However, induration furnaces are described by distributed-parameter models that require long computation times. The performance of IMCoptimization [1], an easy to implement static nonlinear optimization algorithm, is compared to a direct optimization based on the nonlinear process model itself. For a simulated induration furnace, it is shown that the accuracy obtained with the IMC-optimization algorithm is quite sufficient and does not require considerable computation efforts.