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Network synchronization under distributed delayed impulsive control: Average delayed impulsive weight approach
Affiliation:1. School of Mathematics and Statistics, Shandong Normal University, Ji’nan 250014, PR China;2. Center for Control and Engineering Computation, Shandong Normal University, Ji’nan 250014, PR China;3. School of Mathematics, and Research Center for Complex Systems and Network Sciences, Southeast University, Nanjing 210096, PR China;1. School of Mathematics and Statistics, Shandong Normal University, Ji’nan, 250014, PR China;2. School of Automation and Electrical Engineering, Linyi University, Linyi 276005, PR China;1. School of Mathematics and Statistics, Shandong Normal University, Ji’nan 250014, PR China;2. Center for Control and Engineering Computation, Shandong Normal University, Ji’nan 250014, PR China
Abstract:This paper mainly investigates synchronization of complex dynamical networks (CDNs) with both system delay and coupled delay through distributed delayed impulsive control. Instead of constraining the impulsive weight and impulsive delay one by one, a new concept of average delayed impulsive weight is proposed to obtain more relaxed conditions. Subsequently, based on the impulsive control topology, Lyapunov theory and linear matrix inequality (LMI) design, certain flexible criteria of global exponential synchronization (GES) are given and the corresponding convergence rate is estimated. It is interesting to see that the CDNs can still achieve synchronization under comprehensive conditions though impulsive weights work negatively. Namely, the delays in impulsive control are able to promote synchronization potentially. Finally, simulations are given to show that the distributed delayed impulsive control can not only speeds up the convergence rate for synchronized networks, but also facilitates synchronization for desynchronized networks. In addition, the obtained results can be applied to unmanned craft systems.
Keywords:Synchronization  Complex dynamical network  Average delayed impulsive weight  Control topology
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