Model Predictive Control for changing economic targets

DANIEL LIMON; ANTONIO FERRAMOSCA; TEODORO ALAMO; ALEJANDRO HERNAN GONZALEZ; DARCI ODLOAK

Conferencia; IFAC Conference on Nonlinear Model Predictive Control 2012 (NMPC'12); 2012

The objective of this paper is to present recent results on model predictive controlfor tracking in the context of economic operation of a industrial plant. The well-establishedhierarchical economic control is based on a Real Time Optimizer that calculates the economictarget to the advanced controller, in this case model predictive controllers. The change ofthe economic parameters or constraints, or the existence of disturbances and modelling errorsmake that this target may change throughout the plant evolution. The MPC for tracking isan appealing formulation to deal with this issue since maintain the recursive feasibility andconvergence under any change of the target. Thus, this MPC formulation is summarized as wellas its properties. In virtue of these properties, it is demonstrated how the economic operationcan be improved by integrating the Steady State Target Optimizer in the MPC. Then it isalso shown how the proposed MPC can deal with practical problems such us zone control ordistributed control. Finally, the economic control of the plant can be enhanced by adoptingan economic MPC approach. A formulation capable to ensure economic optimality and targettracking is also shown.