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Research Article | Open Access

Iterative learning algorithms for boundary tracing problems of nonlinear fractional diffusion equations

Jungang Wang( )Qingyang SiJun BaoQian Wang
School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an, Shaanxi 710129, P. R. China
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Abstract

In this paper, the iterative learning control technique is extended to distributed parameter systems governed by nonlinear fractional diffusion equations. Based on P-type and P I θ -type iterative learning control methods, sufficient conditions for the convergences of systems are given. Finally, numerical examples are presented to illustrate the efficiency of the proposed iterative schemes. The numerical results show that the closed-loop iterative learning control scheme converges faster than the open-loop iterative learning control scheme and the P I θ -type iterative learning control scheme converges faster than the P-type and the P I-type iterative learning control scheme.

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Networks and Heterogeneous Media
Pages 1355-1377

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Cite this article:
Wang J, Si Q, Bao J, et al. Iterative learning algorithms for boundary tracing problems of nonlinear fractional diffusion equations. Networks and Heterogeneous Media, 2023, 18(3): 1355-1377. https://doi.org/10.3934/nhm.2023059

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Received: 17 December 2022
Revised: 25 February 2023
Accepted: 04 May 2023
Published: 15 September 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)