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Modelling and Estimation for Uncertain Systems with Transmission Delays, Packet Dropouts, and Out-of-Order Packets

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Listed:
  • Li Liu
  • Aolei Yang
  • Wenju Zhou
  • Wasif Naeem
  • Gang Wang
  • Hua Wang

Abstract

The study focuses on the modelling and estimation of a class of discrete-time uncertain systems, including network-induced random delays, packet dropouts, and out-of-order packets during the data transmission from the plant to the estimator. In order to improve system performance, event-triggered signal selection method is used to establish the system model. Based on this model, a distributed measurement and centralized fusion estimation scheme is designed using a robust finite horizon Kalman-type filter. Since the phenomena caused by the network-induced deteriorate estimation accuracy, a time-based reorganization measurement is employed to design a linear delay compensation strategy based on estimation. Moreover, in order to obtain the optimal linear estimation, weighted fusion estimation approach is used to perform information collaboration through the error cross-covariance matrix. Simulation results demonstrate that the proposed method has higher estimation performance than the existing methods in this study.

Suggested Citation

  • Li Liu & Aolei Yang & Wenju Zhou & Wasif Naeem & Gang Wang & Hua Wang, 2018. "Modelling and Estimation for Uncertain Systems with Transmission Delays, Packet Dropouts, and Out-of-Order Packets," Complexity, Hindawi, vol. 2018, pages 1-15, October.
    • Handle: RePEc:hin:complx:7531547
    DOI: 10.1155/2018/7531547
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    References listed on IDEAS

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    1. Shuli Sun & Wendong Xiao, 2013. "Optimal linear estimators for systems with multiple random measurement delays and packet dropouts," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(2), pages 358-370.
    2. Dmitry Brizhinev & Nathan Ryan & Roger Bradbury, 2018. "Modelling Hegemonic Power Transition in Cyberspace," Complexity, Hindawi, vol. 2018, pages 1-13, April.
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