System reliability aware Model Predictive Control framework

Jean C. Salazar, Philippe Weber, Fatiha Nejjari, Ramon Sarrate and Didier Theilliol

Reliability Engineering and System Safety, 2017, vol. 167, issue C, 663-672

Abstract: This paper 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.

Keywords: Reliability; Dynamic Bayesian networks; Model Predictive Control; Reliability Importance Measures; Health-Aware Control (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:167:y:2017:i:c:p:663-672

DOI: 10.1016/j.ress.2017.04.012

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