CONICET | Buscador de Institutos y Recursos Humanos

tEconomic Model Predictive Controllers, consisting of an economic criterion as stage cost for the dynamic regulation problem, have shown to improve the economic performance of the controlled plant. However,throughout the operation of the plant, if the economic criterion changes ? due to variations of prices,costs, production demand, market fluctuations, reconciled data, disturbances, etc. ? the optimal operationpoint also changes. In industrial applications, a nonlinear description of the plant may not be available,since identifying a nonlinear plant is a very difficult task. Thus, the models used for prediction are ingeneral linear. The nonlinear behavior of the plant makes that the controller designed using a linearmodel (identified at certain operation point) may exhibit a poor closed-loop performance or even loss offeasibility and stability when the plant is operated at a different operation point. A way to avoid this issueis to consider a collection of linear models identified at each of the equilibrium points where the plant willbe operated. This is called a multi-model description of the plant. In this work, a multi-model economicMPC is proposed, which takes into account the uncertainties that arise from the difference betweennonlinear and linear models, by means of a multi-model approach: a finite family of linear models isconsidered (multi-model uncertainty), each of them operating appropriately in a certain region arounda given operation point. Recursive feasibility, convergence to the economic setpoint and stability areensured. The proposed controller is applied in two simulations for controlling an isothermal chemicalreactor with consecutive-competitive reactions, and a continuous flow stirred-tank reactor with parallelreactions.