Title :
Modeling and model predictive control of a de-manufacturing plant
Author :
Cataldo, A. ; Scattolini, Riccardo
Author_Institution :
Inst. of Ind. Technol. & Autom., Milan, Italy
Abstract :
Dynamic pallet routing optimal control is a crucial task for evolutionary manufacturing plants in order to guarantee efficient production plant performances. In this paper, a new approach based on hybrid Model Predictive Control (MPC) is proposed to control a manufacturing multitarget, multi-pallet transport line. The mathematical representation of the plant is based on a Mixed Linear Dynamical (MLD) model, used by MPC to predict the plant behavior in terms of the future evolution of the state and control variables. The performance index to be minimized is linear and weights the distance of the pallets from their final target. The resulting Mixed Linear Integer Programming (MILP) problem is recursively solved to obtain the control law. Many simulation experiments have been carried out to evaluate the performances of the proposed approach in a realistic scenario. The achieved results confirm the good performances of the control algorithm and its ability to manage even pallet route conflicts and target dynamic re-scheduling.
Keywords :
industrial plants; integer programming; linear programming; optimal control; palletising; performance index; predictive control; scheduling; MILP problem; MLD model; demanufacturing plant; dynamic pallet routing optimal control; dynamic rescheduling; evolutionary manufacturing plants; hybrid MPC; hybrid model predictive control; mixed linear dynamical model; mixed linear integer programming problem; multipallet transport line; performance index; plant mathematical representation; production plant performances; Control systems; Indexes; Load modeling; Manufacturing; Mathematical model; Nickel; Simulation;
Conference_Titel :
Control Applications (CCA), 2014 IEEE Conference on
Conference_Location :
Juan Les Antibes
DOI :
10.1109/CCA.2014.6981583