The global convergence of some self-scaling conjugate gradient methods for monotone nonlinear equations with application to 3DOF arm robot model

Sulaiman M Ibrahim, Lawal Muhammad, Rabiu Bashir Yunus, Muhammad Yusuf Waziri, Saadi bin Ahmad Kamaruddin, Aceng Sambas, Nooraini Zainuddin and Ali F Jameel

PLOS ONE, 2025, vol. 20, issue 1, 1-36

Abstract: Conjugate Gradient (CG) methods are widely used for solving large-scale nonlinear systems of equations arising in various real-life applications due to their efficiency in employing vector operations. However, the global convergence analysis of CG methods remains a significant challenge. In response, this study proposes scaled versions of CG parameters based on the renowned Barzilai-Borwein approach for solving convex-constrained monotone nonlinear equations. The proposed algorithms enforce a sufficient descent property independent of the accuracy of the line search procedure and ensure global convergence under appropriate assumptions. Numerical experiments demonstrate the efficiency of the proposed methods in solving large-scale nonlinear systems, including their applicability to accurately solving the inverse kinematic problem of a 3DOF robotic manipulator, where the objective is to minimize the error in achieving a desired trajectory configuration.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0317318 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 17318&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0317318

DOI: 10.1371/journal.pone.0317318

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().