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 multi-target, 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

Modeling and model predictive control of a de-manufacturing plant

Andrea Cataldo;
2014

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 multi-target, 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
2014
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
Model Predictive Control
Manufacturing system
Control optimization
Control model based
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/223502
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