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Research Article | Open Access

A pseudo-spectral approach for optimal control problems of variable-order fractional integro-differential equations

Zahra Pirouzeh1Mohammad Hadi Noori Skandari2( )Kamele Nassiri Pirbazari1Stanford Shateyi3( )
Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
Department of Applied Mathematics, University of Venda, P. Bag X5050, Thohoyandu, Limpopo 950, South Africa
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Abstract

Nonlinear optimal control problems governed by variable-order fractional integro-differential equations constitute an important subgroup of optimal control problems. This group of problems is often difficult or impossible to solve analytically because of the variable-order fractional derivatives and fractional integrals. In this article, we utilized the expansion of Lagrange polynomials in terms of Chebyshev polynomials and the power series of Chebyshev polynomials to find an approximate solution with high accuracy. Subsequently, by employing collocation points, the problem was transformed into a nonlinear programming problem. In addition, variable-order fractional derivatives in the Caputo sense were represented by a new operational matrix, and an operational matrix represented fractional integrals. As a result, the mentioned integro-differential optimal control problem becomes a nonlinear programming problem that can be easily solved with the repetitive optimization method. In the end, the proposed method is illustrated by numerical examples that demonstrate its efficiency and accuracy.

CLC number: 34K37, 49M25, 49M37

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AIMS Mathematics
Pages 23692-23710

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Cite this article:
Pirouzeh Z, Skandari MHN, Pirbazari KN, et al. A pseudo-spectral approach for optimal control problems of variable-order fractional integro-differential equations. AIMS Mathematics, 2024, 9(9): 23692-23710. https://doi.org/10.3934/math.20241151

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Received: 16 February 2024
Revised: 12 June 2024
Accepted: 14 June 2024
Published: 15 September 2024
©2024 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)