PD Control with Auto-Tuned Gains Using Rbf Networks for Enhanced Trajectory Tracking in Manipulator Robots Cover

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PD Control with Auto-Tuned Gains Using Rbf Networks for Enhanced Trajectory Tracking in Manipulator Robots

Acta Mechanica et Automatica

Volume 19 (2025): Issue 4 (December 2025)

By: Carlos MUÑIZ-MONTERO , Luis A. SÁNCHEZ-GASPARIANO and Javier LEMUS-LÓPEZ

Open Access

|Dec 2025

Authors

Carlos MUÑIZ-MONTERO

carlos.muniz@uppuebla.edu.mx

Academic Program of Electronics and Telecommunications, Polytechnic University of Puebla, Puebla, Mexico

Luis A. SÁNCHEZ-GASPARIANO

luis.sanchezgas@correo.buap.mx

Faculty of Electronic Sciences, Benemérita Universidad Autónoma de Puebla, Pue, Mexico

Javier LEMUS-LÓPEZ

javier.lemus@uppuebla.edu.mx

Academic Program of Electronics and Telecommunications, Polytechnic University of Puebla, Puebla, Mexico

DOI: https://doi.org/10.2478/ama-2025-0070 | Journal eISSN: 2300-5319 | Journal ISSN: 1898-4088

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Language: English

Page range: 617 - 625

Submitted on: Sep 21, 2024

|

Accepted on: Oct 5, 2025

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Published on: Dec 19, 2025

Published by: Bialystok University of Technology

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

Radial Basis Function Networks,

trajectory tracking,

Lyapunov stability

Related subjects:

Electrical engineering,

Mechanical engineering,

Bioengineering and biomedical engineering,

Civil engineering,

Environmental engineering

© 2025 Carlos MUÑIZ-MONTERO, Luis A. SÁNCHEZ-GASPARIANO, Javier LEMUS-LÓPEZ, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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