Fault-tolerant synchronization of drive-response memristive competitive neural networks with multiple actuator failures

In this article, the synchronization of drive-response memristive competitive neural networks (MCNNs) under multiple actuator failures is studied through implementing fault-tolerant control scheme. Unlike previous studies,the actuator failures considered in this paper include both bias and
effectiveness failures. To address these challenges, a proper mathematical model is firstly established to capture the impact of actuator failures on control inputs. Subsequently, several sufficient conditions are deduced by designing an appropriate bilayer fault-tolerant controller and constructing a Lyapunov functional to achieve the global exponential synchronization, finite-time synchronization, fixed-time synchronization and predefined-time synchronization respectively. Additionally, the settling time upper bounds for the proposed synchronization methods are determined. In the end, numerical simulations with analysis and comparison are performed to confirm the validity of the proposed results.