Disturbance-Induced Fault Detection of Boolean Control Networks

Abstract

This letter investigates the fault detection problem of Boolean control networks (BCNs) induced by disturbance nodes. Firstly, the state transition matrix of the BCNs is decomposed into an interpretable sub-block structure, based on which a stability criterion for the system state space is formulated. By analyzing the mapping between input nodes and sub-blocks, a new anti-disturbance matrix is constructed to solve the system disturbance problem. Subsequently, a rank-based fault detection method is proposed, together with a verification matrix that enables the identification of disturbance-induced faults in the BCNs. Compared with existing methods, our approach significantly reduces the space complexity. Finally, the effectiveness and practicality of the proposed method are validated through an industrial sorting and packaging case study.