Composite Anti-Disturbance Synchronization Control for Delayed Neural Networks Subject to Unknown Disturbances - Wang, Ting; Chen, Linbo; Li, Tao; Fei, Shumin (Circuits, systems, and signal processing, 2021)
This paper studies the master–slave synchronization in a class of delayed neural networks under external disturbance. Initially, based on an exogenous disturbance model, an effective observer is proposed to estimate the disturbance and the estimation is further utilized to design the composite controller. Then, as for the overall closed-loop error system, by choosing an augmented Lyapunov–Krasovskii functional and using some recently reported techniques, a sufficient condition is established to guarantee the desired stability and H ∞ control performance. Furthermore, by combining free-weighting matrix technique with matrix transformation one, two co-design methods are obtained to ensure the existence of observer gain and controller ones in terms of linear matrix inequalities, which can possess much less conservatism. Finally, some comparisons and simulations in an example are given to illustrate our proposed methods.