Reliability-based economic model predictive control for generalised flow-based networks including actuators' health-aware capabilities
Juan M. Grosso ; Carlos Ocampo-Martinez ; Vicenç Puig
International Journal of Applied Mathematics and Computer Science, Tome 26 (2016), p. 641-654 / Harvested from The Polish Digital Mathematics Library

This paper proposes a reliability-based economic model predictive control (MPC) strategy for the management of generalised flow-based networks, integrating some ideas on network service reliability, dynamic safety stock planning, and degradation of equipment health. The proposed strategy is based on a single-layer economic optimisation problem with dynamic constraints, which includes two enhancements with respect to existing approaches. The first enhancement considers chance-constraint programming to compute an optimal inventory replenishment policy based on a desired risk acceptability level, leading to dynamical allocation of safety stocks in flow-based networks to satisfy non-stationary flow demands. The second enhancement computes a smart distribution of the control effort and maximises actuators' availability by estimating their degradation and reliability. The proposed approach is illustrated with an application of water transport networks using the Barcelona network as the case study considered.

Publié le : 2016-01-01
EUDML-ID : urn:eudml:doc:286725
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     title = {Reliability-based economic model predictive control for generalised flow-based networks including actuators' health-aware capabilities},
     journal = {International Journal of Applied Mathematics and Computer Science},
     volume = {26},
     year = {2016},
     pages = {641-654},
     language = {en},
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Juan M. Grosso; Carlos Ocampo-Martinez; Vicenç Puig. Reliability-based economic model predictive control for generalised flow-based networks including actuators' health-aware capabilities. International Journal of Applied Mathematics and Computer Science, Tome 26 (2016) pp. 641-654. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv26i3p641bwm/

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