Title :
A Mixed Logical Dynamic Model Predictive Control approach for handling industrially relevant transportation constraints
Author :
Braun, Martin W. ; Shear, Joanna
Author_Institution :
Customer Planning & Logistics Group, Intel Corp., Chandler, AZ, USA
Abstract :
Model Predictive Control (MPC) offers an attractive way to systematically address uncertainty in demand forecasts, factory execution, or external supply and effectively mitigate potential under-damped responses in the closed-loop system. However, other practical concerns may preclude the use of classical formulations of MPC. Of particular importance is the ability to ship material through auxiliary shipping lanes when either material is not available from the primary node, or shipping capacity is constrained in the primary shipping lane. To meet unforecasted demand, a controller must also make judicious use of priority shipping. The inclusion of Mixed Logical Dynamics (MLD) into the MPC formulation allows these logical decisions to be made in a systematic way, without requiring input from the user in real-time. In this paper, an MLD extension is made to a state-space MPC formulation to deal effectively with practical shipping considerations. Performance of the proposed approach is demonstrated in a number of realistic scenarios.
Keywords :
closed loop systems; constraint handling; demand forecasting; logistics; predictive control; transportation; uncertain systems; auxiliary shipping lanes; closed loop system; demand forecasts; external supply; factory execution; industrially relevant transportation constraints; mixed logical dynamic model predictive control; primary shipping lane; priority shipping; uncertainty; under damped responses; Equations; Marine vehicles; Materials; Mathematical model; Predictive models; Supply chains; Uncertainty;
Conference_Titel :
Automation Science and Engineering (CASE), 2010 IEEE Conference on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4244-5447-1
DOI :
10.1109/COASE.2010.5584165