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Event-triggered sampling scheme for pinning control in multi-agent networks with general nonlinear dynamics

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Abstract

Event-triggered control strategy of complex dynamical networks is motivated by further applications of embedded microprocessors equipped in the nodes with limited computation and storage resources that gather information and actuate the individual controller updates. One expects that the numbers of controller updates and measurement broadcasts decrease significantly. This paper presents a novel framework of distributed event-triggered asynchronous intermittent communication strategy for pinning controllability in complex dynamical directed networks in which each node is equipped with nonlinear dynamics with or without time delay. The proposed method extends the previous works on pinning control by considering limited communication capacities through strictly noncontinuous decentralized information exchange and considers the existing continuous control schemes as special cases when the corresponding tuning parameters in the designed events are equal to zeros. Based on properties of M-matrices, some analytical criteria are established to guarantee that all follower nodes in a network can globally asymptotically converge to a homogenous state of a leader node. Control inputs exerted on all follower nodes are only triggered at their individual event instants, which reduce the amount of communication in information channels and lower the frequency of controller updates to favor a digital implementation. A positive lower bound for the broadcasting period, i.e., the difference between two successive broadcasting time instants, can be achieved, which excludes the Zeno triggering behavior before the synchronization is achieved. Simulation results show effectiveness of the proposed approach and illustrate correctness of the theoretical results.

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Acknowledgments

The work described in this paper was supported in part by the Fundamental Research Funds for the Central Universities under Grants XDJK2014C117 and SWU114006, in part by the Natural Science Foundation Project of Chongqing CSTC under Grants cstc2014jcyjA40016 and cstc2014jcyjA40041, and in part by the Natural Science Foundation of China under Grant 61403314.

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Authors and Affiliations

  1. School of Electronic and Information Engineering, Southwest University, Chongqing, 400715, People’s Republic of China

    Huaqing Li

  2. School of Electrical and Information Engineering, The University of Sydney, Sydney, 2006, Australia

    Guo Chen

  3. Department of Mathematics and Information Engineering, Chongqing University of Education, Chongqing, 400067, People’s Republic of China

    Li Xiao

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  1. Huaqing Li
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  2. Guo Chen
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  3. Li Xiao
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Correspondence to Huaqing Li.

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Li, H., Chen, G. & Xiao, L. Event-triggered sampling scheme for pinning control in multi-agent networks with general nonlinear dynamics. Neural Comput & Applic 27, 2587–2599 (2016). https://doi.org/10.1007/s00521-015-2027-4

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  • DOI: https://doi.org/10.1007/s00521-015-2027-4

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