Reliability–based economic model predictive control for generalised flow–based networks including actuators’ health–aware capabilities

Abstract

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.

Review of Post-Prognostics Decision-Making in Prognostics and Health Management

“…The system is controlled by a LQR in which its parameters are adapted using the degradation level of the actuators through its RUL. Grosso et al (Grosso, Ocampo-Martinez, & Puig, 2016) proposed an improved reliabilitybased economic model predictive control strategy that is similar to the predictive control proposed by Pereira et al in (Pereira et al, 2010). The idea consists of computing and distributing the remaining allowed degradation level on the remaining time to maintenance but with an additive dynamic stock policy in the optimization problem.…”

Reconfiguration of large-scale systems using back-up components

“…Basically, flow-based networks are conformed by a combination of flow sources, flow handling components, sinks, nodes, links and storage elements ( Grosso Pérez, 2015 ). The control-oriented model of flow-based networks may be described by means of a set of linear (or linearised) discrete difference-algebraic equations (DAE) ( Grosso et al, 2014 ).…”

A Hybrid Approach to Process Planning: The Urban Traffic Controller Example

“…MPC has been implemented in a variety of applications ranging from production planning (Mezghiche et al, 2015;Baldea et al, 2015); industrial production (Zhu et al, 2015;Alanqar et al, 2017;Grosso et al, 2016) and supply chain (Chu and You, 2015;Schildbach and Morari, 2016); intelligent Transport Systems (Mahalingam and Agrawal, 2016;Roncoli et al, 2016); agriculture (Graf Plessen and Bemporad, 2017) and robot manipulation in path planning (Ji et al, 2017;Joos et al, 2017).…”