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System reliability aware Model Predictive Control framework
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DOI：10.1016/j.ress.2017.04.012.png)
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Abstract
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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. (C) 2017 Elsevier Ltd. All rights reserved.
Keywords:
Reliability
Dynamic Bayesian networks
Model Predictive Control
Reliability Importance Measures
Health-Aware Control
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