MPC, objective function with economic cost

Abstract

The distillation is a common method with great energy expenditure used for separation in the oil, food, chemical, etc. However, the technology currently used today in the distillation process is not very different from that used in the first distillation columns in the 19th century. The requirements of thermal energy in the distillation process are enormous. The thermodynamic efficiency of the distillation process is less than 10%. It is estimated that 8% of all energy used by U.S. industries is consumed in the distillation process. Energy is responsible for 50 to 60% of the operating costs of refineries while in chemical that proportion varies from 30 to 40%. These data shows the potential of savings that the distillation process can be achieved when the process is subjected to better control and optimized. The Model Based Predictive Control (MPC) is an advanced control technique with features that solve operational problems present in distillation columns. The MPC can deal with of multivariable systems with interactions and considerable dead times, nonlinearities and restrictions on the variables. One of the most important steps in the MPC is the minimization of an objective function. Different types of objective functions can be used in the MPC control algorithm with specific parameter settings for each type of objective function. In this work, the Wood-Berry model for distillation columns will be used. One MPC control strategy for column using a objective function with economic cost will be implemented. Finally, they will be made adjustments to the parameters of the objective function in order to see how these settings influence the response of the MPC controller.