Reliability Assessment Model for Industrial Control System Based on Belief Rule Base

Yuhe Wang, Peili Qiao, Zhiyong Luo, Guanglu Sun, Guangze Wang

Abstract


This paper establishes a novel reliability assessment method for industrial control system (ICS). Firstly, the qualitative and quantitative information were integrated by evidential reasoning(ER) rule. Then, an ICS reliability assessment model was constructed based on belief rule base (BRB). In this way, both expert experience and historical data were fully utilized in the assessment. The model consists of two parts, a fault assessment model and a security assessment model. In addition, the initial parameters were optimized by covariance matrix adaptation evolution strategy (CMA-ES) algorithm, making the proposed model in line with the actual situation. Finally, the proposed model was compared with two other popular prediction methods through case study. The results show that the proposed method is reliable, efficient and accurate, laying a solid basis for reliability assessment of complex ICSs.

Keywords


Belief rule base (BRB), industrial control system (ICS), evidential reasoning (ER), reliability assessment, covariance matrix adaptation evolution strategy (CMA-ES) algorithm

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References


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DOI: https://doi.org/10.15837/ijccc.2019.3.3548



Copyright (c) 2019 Yuhe Wang, Peili Qiao, Zhiyong Luo, Guanglu Sun, Guangze Wang

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