Multiple Memristor Circuit Parametric Fault Diagnosis Using Feedback-Control Doublet Generator

The memristor was first theorized as an electrical element, which provided the missing link between the charge and the flux. Due to the advantages of nano-scale size, multiple interconnected memristors have demonstrated unique overall characteristics, which are ideal for the utilization in neuromorphic systems. However, compared with the individual memristor circuit, a little work is explored about the overall behavior of the multiple memristive systems. In particular, the lack of a fault diagnosis approach for composite memristive network structures makes all the corresponding applications unstable and shaky. In this paper, the extraordinary properties of multiple memristor circuits are further investigated with comprehensive formula derivation and scientific computer simulations. Furthermore, a special feedback-control doublet generator is designed for implementing the fuzzy-based parametric fault diagnosis of multiple memristor circuits, which offers huge benefits in terms of accuracy and time consumption. Finally, the entire scheme is validated by an illustrative example.