The primary objective of the present paper is to develop an approach for analyzing pinning synchronization stability in a complex delayed dynamical network with directed coupling. Some simple yet generic criteria for pinning such coupled network are derived analytically. Compared with some existing works, the primary contribution is that the synchronization manifold could be chosen as a weighted average of all the nodes states in the network for the sake of practical control tactics, which displays the different influences and contributions of the various nodes in synchronization seeking processes of the dynamical network. Furthermore, it is shown that in order to drive a complex network to a desired synchronization state, the coupling strength should vary according to the controller. In addition, the theoretical results about the time-invariant network is extended to the time-varying network, and the result on synchronization problem can also be extended to the consensus problem of networked multi-agent systems. Subsequently, the theoretic results are illustrated by a typical scale-free (SF) neuronal network. Numerical simulations with three kinds of the homogenous solutions, including an equilibrium point, a periodic orbit, and a chaotic attractor, are finally given to demonstrate the effectiveness of the proposed control methodology.
This paper is concerned with impulsive practical synchronization in a class of n-dimensional nonautonomous dynamical systems with parameter mismatch. Some simple yet general algebraic synchronization criteria are derived based on the developed practical stability theory on impulsive dynamical systems. A distinctive feature of this work is that the impulsive control strategy is used to make n-dimensional nonautonomous dynamical systems with parameter mismatch achieve practical synchronization, where the parameter mismatch likewise exist in both system parameters and external excitation ones, and the synchronization error bound can be estimated by an analytical expression. Subsequently, the obtained results are applied to a typical gyrostat system, and numerical simulations demonstrate the effectiveness of the criteria and the robustness of the control technique.