Two-Side Data Dropout for Linear Deterministic Systems

  • Dong Shen


This chapter contributes to the convergence analysis of ILC for linear systems under general data dropouts at both measurement and actuator sides. By using a simple compensation mechanism for the dropped data, the sample path behavior of the input sequence along the iteration axis is analyzed and formulated as a Markov chain first. Based on the Markov chain, the recursion of the input error is reformulated as a switching system, and then a novel convergence proof is established in the almost sure sense under mild design conditions.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.College of Information Science and TechnologyBeijing University of Chemical TechnologyBeijingChina

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