Open AccessOn Iterative Learning Control for Remote Control Systems with Packet Losses
Author(s) -
Chunping Liu,
Rong Xiong,
JianXin Xu,
Jun Wu
Publication year - 2013
Publication title -
journal of applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.307
H-Index - 43
eISSN - 1687-0042
pISSN - 1110-757X
DOI - 10.1155/2013/245372
Subject(s) - iterative learning control , dropout (neural networks) , control theory (sociology) , network packet , bernoulli distribution , computer science , convergence (economics) , bernoulli's principle , actuator , transmission delay , transmission (telecommunications) , scheme (mathematics) , mathematics , control (management) , random variable , engineering , artificial intelligence , computer network , telecommunications , mathematical analysis , statistics , machine learning , aerospace engineering , economics , economic growth
The problem of iterative learning control (ILC) is consideredfor a class of time-varying systems with random packet dropouts. It is assumed that an ILC scheme is implemented via a remote control systemand that packet dropout occurs during the packet transmission between the ILC controller and the actuator ofremote plant. The packet dropout is viewed as a binary switching sequence which is subject to the Bernoulli distribution. In order to eliminate the effect of packet dropouts on the convergence property of output error,the hold-input scheme is adopted to compensate the packet dropout at the actuator. It is shown that the hold-input scheme with average ILC can achieve asymptotical convergencealong the iteration axis for discrete time-varying linear system. Numerical examples are provided to show the effectiveness of the proposed method
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