Random Sequence Model for Nonlinear Systems with Unknown Control Direction

Chapter

Abstract

The iterative learning control is constructed for the discrete-time networked nonlinear systems with random data dropout at the measurement side and unknown control direction, which have not been studied simultaneously in literature. A novel regulating approach based on truncations is introduced to make the proposed algorithm find the correct control direction adaptively, and then guarantee the almost sure convergence property.

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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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