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Consensus in networked dynamical systems with event-triggered control inputs and random switching topologies

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Abstract

Event-triggered control approaches of networked control systems are motivated by applications of embedded microprocessors with limited computation and storage resources . This paper investigates an event-triggered consensus control scheme with random switching directed topologies and time-varying transmission delay in a general class of networked control systems. A distributed sampling scheme triggering at node’s independent time instants is designed for updates of control inputs. The desired properties of the resulted error dynamical system, such as stability and convergence can be preserved. It is not only proven that the event-triggered consensus is reachable, but also given an estimation of the convergence rate. It is shown that before the consensus is achieved, the inner-event interval is lower bounded by a positive constant, which excludes the Zeno behavior. The results are also applied to other special cases including time-delay free, fixed topology and leader-following consensus cases. Numerical simulation examples are presented to demonstrate the correctness of the theoretical results.

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Acknowledgments

The authors highly appreciate the Associate Editor and anonymous reviewers’ great efforts in reviewing our manuscript and for providing many helpful comments and suggestions. The work described in this paper was supported in part by the Zhejiang Open Foundation of the Most Important Subjects, 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, in part by the scientific and technological research program of Chongqing Municipal Education Commission under Grant KJ1501401, and in part by the Natural Science Foundation of China under Grant 61403314.

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Li, H., Wang, Y., Chen, G. et al. Consensus in networked dynamical systems with event-triggered control inputs and random switching topologies. Neural Comput & Applic 28, 1095–1108 (2017). https://doi.org/10.1007/s00521-015-2117-3

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  • DOI: https://doi.org/10.1007/s00521-015-2117-3

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