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Research Article | Open Access

A scaled Polak-Ribi e ` re-Polyak conjugate gradient algorithm for constrained nonlinear systems and motion control

Jamilu Sabi'u1Ali Althobaiti2Saad Althobaiti3Soubhagya Kumar Sahoo4Thongchai Botmart5( )
Department of Mathematics, Yusuf Maitama Sule University Kano, PMB 3220, Kano Nigeria
Mathematics Department, College of Science, Taif University, P.O.Box 11099, Taif 21944, Saudi Arabia
Department of Sciences and Technology, Ranyah University Collage, Taif University, P.O.Box 11099, Taif 21944, Saudi Arabia
Department of Mathematics, Institute of Technical Education and Research, Siksha O Anusandhan University, Bhubaneswar 751030, Odisha, India
Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand
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Abstract

This paper proposes Polak-Ribi e ` re-Polyak (PRP) conjugate gradient (CG) directions based on two efficient scaling strategies. The first scaling parameter is determined by approaching the quasi-Newton direction, and the second by utilizing the well-known Barzilai-Borwein approach. In addition, we proposed two directions that satisfy the sufficient descent criterion regardless of the line search strategy. The proposed directions lead to a matrix-free algorithm for solving monotone-constrained nonlinear systems. The proposed algorithm's global convergence analysis is presented using some underlying assumptions. Furthermore, a detailed numerical comparison with other existing algorithms revealed that the proposed algorithm is both efficient and effective. Finally, the proposed technique is applied to the motion control problem of a two-joint planar robotic manipulator.

CLC number: 90C26, 90C30

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AIMS Mathematics
Pages 4843-4861

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Cite this article:
Sabi'u J, Althobaiti A, Althobaiti S, et al. A scaled Polak-Ribi e ` re-Polyak conjugate gradient algorithm for constrained nonlinear systems and motion control. AIMS Mathematics, 2023, 8(2): 4843-4861. https://doi.org/10.3934/math.2023241

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Received: 14 September 2022
Revised: 15 November 2022
Accepted: 05 December 2022
Published: 15 February 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)