Work

A new scaled BFGS method for convex constraints monotone systems: Applications in motion control

Year: 2024

Type: article

Abstract: This paper introduces a new version of the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm, characterized as a scaled memoryless, projection-based, and derivative-free method for finding approximate solutions of monotone nonlinear equations with convex constraints. The optimal value of the scaling parameter is achieved by minimizing the BFGS update matrix. The theoretical analysis is performed to demonstrate the global convergence of the approach. Numerical analysis and comparisons with prior results indicate that the proposed approach has superior performance for CPU time, iteration count, and function evaluations. The new algorithm is used to solve the motion control issue of a two-jointed coplanar robot manipulator.

Source: Results in Applied Mathematics

DOI: 10.1016/j.rinam.2024.100531

Authors: Abdullah Shah, Maaz ur Rehman, Jamilu Sabi’u, Muhammad Sohaib, Khaled M. Furati

Institutions: King Fahd University of Petroleum and Minerals, COMSATS University Islamabad, Maitama Sule University Kano

Language: English

Topic: Iterative Methods for Nonlinear Equations

Subfield: Numerical Analysis

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,490

Funder: King Fahd University of Petroleum and Minerals