System reliability aware Model Predictive Control framework

Abstract

This work presents a Model Predictive Control (MPC) framework taking into account the usage of the actuators to preserve system reliability while maximizing control performance. Two approaches are proposed to preserve system reliability: a global approach that integrates in the control algorithm a representation of system reliability, and a local approach that integrates a representation of component reliability. The trade-off between the system reliability and the control performance should be taken into account. A methodology for MPC tuning is proposed to handle this trade-off. System and component reliability are computed based on Dynamic Bayesian Network. The effectiveness and benefits of the proposed control framework are discussed through its application to an over-actuated system.

Optimal sensor placement based on multiattribute decision-making considering the common cause failure

“…RAW of a component X i can be computed by equation (9) where RAW i represents the risk achievement worth for a component X i ; P(S={F}|Xi={F}) is the system failure probability given that a component X i has failed; P(S={F}) is the probability of system failure. (iii) BIM represents the probability that the failure of a component X i coincide with the failure of the system. 41 This can be explained as the decrease of system reliability when the component changes from a working state to a failure state. The calculation formula of BIM is as shown in equation (10) where BIM i is the Birnbaum importance measure for a component X i ; P(S={W}|Xi={W}) is the probability that system in working state when a component X i in working state; P(S={W}|Xi={F}) is the probability that system in working state when a component X i in failure state.…”

Health-aware LPV-MPC Based on System Reliability Assessment for Drinking Water Networks

“…In particular, engineering systems are organized to support varying amounts of loads characterized in terms of usage rate or occupied period. Several observational types of research have established that the function load strongly affects the component failure rate [15]. Hence, it is important to consider the load versus failure rate relationship when presenting system reliability evaluation.…”

“…As described in Section III, the reliability of the DWN can be computed using the control input (pump commands) information. In order to include a new objective in the MPC that aims to increase the system reliability, the reliability model is approximated by means of a linear model (15). The new MPC model uses the following model…”

Special section on ``Applications of probabilistic graphical models in dependability, diagnosis and prognosis''

“…Finally, an application of control with the objective to limit the control effect on failure and unavailability of the system is proposed by Salazar et al [8]. This work presents a Model Predictive Control (MPC) framework taking into account the usage of the actuators to preserve system reliability while maximizing control performance.…”