Unified synchronization and fault‐tolerant anti‐disturbance control for synchronization of multiple memristor‐based neural networks

Abstract

SummaryThis work primarily concentrates on the design of fault‐tolerant anti‐disturbance control for synchronization of multiple memristor‐based neural networks subject to time delay, matched and mismatched disturbances. Moreover, in the addressed network model, we consider parameter uncertainties and actuator faults. Firstly in order to estimate the matched disturbances generated by the exogenous system, a disturbance observer is devised. Whereas, the mismatched part is tackled by employing the mixed and passivity performance indexes. Subsequently, a unified controller is designed by incorporating error feedback control and the disturbance estimate. Further, with the assistance of Lyapunov stability theory and linear matrix inequality technique, an adequate criteria is procured to ascertain the required synchronization criteria for the assayed network model with the mixed and passivity performance indexes. Following this, by basing on the established conditions, the explicit form of the controller and observer gain matrices is obtained. In the end, a numerical example with simulation results is shown to confirm the potential and usefulness of the conclusions acquired from the theoretical analysis.

A New Reaching Law Based Nonsingular Terminal Sliding Mode Control Scheme for the Servo System With Periodic Uncertainties

“…It also needs to be improved. Some recent results on disturbance rejection have been developed in literature [20]- [26]. A robust consensus control method for multi-agent with unknown control directions was developed in [20] and [21].…”

“…Actuator saturations, immeasurable states and other uncertainties were also taken into consideration, anti-windup compensator-based and proportional integral observer-based controllers were developed respectively, which can guarantee the stability of the systems. In [26], the synchronization problem of multiple memristor-based neural networks with disturbances, parameter uncertainties and actuator faults was studied, and observer-based estimator and H-infinity control method were incorporated in the unified controller to deal with matched and mismatched disturbances respectively. However, these methods are not specifically designed for periodic unmodeled dynamics, thus, they are less suitable for the operating situations that the load torque spans a wide range.…”