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Vestnik YuUrGU. Ser. Mat. Model. Progr., 2020, Volume 13, Issue 2, Pages 69–79 (Mi vyuru544)  

Mathematical Modelling

New P-type and D-type iterative learning control update laws for networked control systems with random data dropouts

S. A. Najafi, A. Delavarkhalafi

Yazd University, Yazd, Iran

Abstract: In this paper, we present two new P-type and D-type iterative learning control (ILC) update laws for linear stochastic systems with random data dropout modeled with a Bernoulli random variable. We prove that the P-type and D-type ILC update laws converge to the desired input in the almost sure sense. We show that the convergence conditions of the inputs corresponding to the P-type and D-type ILC update laws for networked control systems are the same. We present the performance comparison of the P-type and D-type ILC update laws. In this comparison, we conclude that the P-type ILC update law is more effective than the D-type ILC update law for networked control systems.

Keywords: iterative learning control, D-type, P-type, data dropout, networked control linear system.

DOI: https://doi.org/10.14529/mmp200206

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UDC: 517.977.5
MSC: 93Exx
Received: 19.06.2019
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Citation: S. A. Najafi, A. Delavarkhalafi, “New P-type and D-type iterative learning control update laws for networked control systems with random data dropouts”, Vestnik YuUrGU. Ser. Mat. Model. Progr., 13:2 (2020), 69–79

Citation in format AMSBIB
\Bibitem{NajDel20}
\by S.~A.~Najafi, A.~Delavarkhalafi
\paper New P-type and D-type iterative learning control update laws for networked control systems with random data dropouts
\jour Vestnik YuUrGU. Ser. Mat. Model. Progr.
\yr 2020
\vol 13
\issue 2
\pages 69--79
\mathnet{http://mi.mathnet.ru/vyuru544}
\crossref{https://doi.org/10.14529/mmp200206}


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