Making non-centralized a model predictive control scheme by using distributed Smith dynamics

Trabajo presentado al 5th IFAC Conference on Nonlinear Model Predictive Control (NMPC) celebrado en Sevilla (España) del 17 al 20 de septiembre de 2015.This paper proposes a non--centralized Model Predictive Control (MPC) scheme for a system comprised by several sub-systems. Operational constraints for each subsystem are considered as well as a single coupled constraint on the control inputs that models a limitation of the emph{resource} supplied by the controller. If the underlying optimization problem is of large-scale nature, traditional MPC suffers from computational burden issues. A cause of this problem is the requirement of having centralized information to guarantee that the computed control actions satisfy the coupled constraint. In this work, a traditional MPC is made non--centralized by means of a strategy based on distributed population dynamics. The proposed methodology divides the problem into several local MPC controllers that coordinate their decisions by using a communication network without the need of a centralized scheme. It is proved that this methodology provides an optimal solution that satisfies both the operational constraints of each sub--system, and the coupled constraint of the control signals. Finally, the proposed method is compared with a traditional centralized MPC in an industrial problem that involves several continuously stirred tank reactors.This work has been partially supported by the projects ECOCIS (Ref. DPI2013-48243-C2-1-R), EFFINET (Ref. FP7-ICT-2011-8-31855), and “Drenaje urbano y cambio climático: Hacia los sistemas de alcantarillados del futuro. Fase II. COLCIENCIAS 633/2013”. J. Barreiro-Gomez and G. Obando are partially supported by Colciencias-Colfuturo. J. Barreiro-Gomez is also partially supported by Agencia de Gestio d’Ajust Universitaris i de Recerca AGAUR.Peer Reviewe