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Event-Triggered State Estimation for Complex Systems with Randomly Nonlinearities and Time-Varying Delay

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Book cover Computational Intelligence, Networked Systems and Their Applications (ICSEE 2014, LSMS 2014)

Abstract

The event-triggered state estimation is investigated for a class of complex networks system with randomly nonlinearities. A novel event-triggered scheme is proposed, which can reduce the information communication burden in the network. Considering the effect of transmission delay, a time-varying delayed system model is constructed. Attention of this paper is focused on the analysis and design of a reliable estimator for the complex networks through the available output measurements under event-triggered scheme. In order to design the state estimator, a Lyapunov functional approach and the linear matrix inequality technique are employed. A sufficient condition is obtained in which the estimator error dynamics is exponential asymptotically stable, and a state estimator of considered complex networks can be achieved by solving some linear matrix inequalities. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

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Tan, Y., Liu, J., Zhang, Y. (2014). Event-Triggered State Estimation for Complex Systems with Randomly Nonlinearities and Time-Varying Delay. In: Fei, M., Peng, C., Su, Z., Song, Y., Han, Q. (eds) Computational Intelligence, Networked Systems and Their Applications. ICSEE LSMS 2014 2014. Communications in Computer and Information Science, vol 462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45261-5_43

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  • DOI: https://doi.org/10.1007/978-3-662-45261-5_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45260-8

  • Online ISBN: 978-3-662-45261-5

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