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Title: Sampled-data synchronization control of dynamical networks with stochastic sampling
Authors: Shen, B
Wang, Z
Liu, X
Keywords: Dynamical networks
Gronwall's inequality
Jenson integral inequality
Sampled-data control
Stochastic sampling
Synchronization control
Publication Date: 2012
Publisher: IEEE
Citation: IEEE Transactions on Automatic Control, 57(10): 2644 - 2650, Oct 2012
Abstract: This technical note is concerned with the sampled-data synchronization control problem for a class of dynamical networks. The sampling period considered here is assumed to be time-varying that switches between two different values in a random way with given probability. The addressed synchronization control problem is first formulated as an exponentially mean-square stabilization problem for a new class of dynamical networks that involve both the multiple probabilistic interval delays (MPIDs) and the sector-bounded nonlinearities (SBNs). Then, a novel Lyapunov functional is constructed to obtain sufficient conditions under which the dynamical network is exponentially mean-square stable. Both Gronwall's inequality and Jenson integral inequality are utilized to substantially simplify the derivation of the main results. Subsequently, a set of sampled-data synchronization controllers is designed in terms of the solution to certain matrix inequalities that can be solved effectively by using available software. Finally, a numerical simulation example is employed to show the effectiveness of the proposed sampled-data synchronization control scheme.
Description: Copyright @ 2012 IEEE
Sponsorship: This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61028008, 60974030, 61134009 and 61104125, the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation of Germany.
ISSN: 0018-9286
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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