Control Vector Parameterization with Sensitivity Based Refinement Applied to Baking Optimization

Abstract

In bakery production product quality attributes as crispness, brownness, crumb and water content are developed by the transformations that occur during baking and which are initiated by heating. A quality driven procedure requires process optimization to improve bakery production and to find operational procedures for new products. Control vector parameterization (CVP) is an effective method for the optimization procedure. However, for accurate optimization with a large number of parameters (representing the control vector), CVP optimization takes a long time for computation. In this work, an improved method for direct dynamic optimization using CVP is presented. The method uses a sensitivity based step size refinement for the selection of control input parameters. The optimization starts with a coarse discretization level for the control input in time. In successive iterations the step size was refined for the parameters for which the performance index has a sensitivity value above a threshold value. With this selection, optimization is continued for a selected group of input parameters while the other non sensitive parameters (below threshold) are kept constant. Increasing the threshold value lowers the computation time, however the obtained performance index becomes less. A threshold value in the range of 10-20% of the mean sensitivity satisfies well. The method gives a better solution for a lower computation effort than single run optimization with a large number of parameters or refinement procedures without selection.