Work

Adaptive Compensation for Bilateral Teleoperation Systems With Asymmetric Time-Varying Delays Using Neural Network in P+d Control Framework

Year: 2025

Type: article

Abstract: Bilateral teleoperation systems face significant challenges in achieving accurate master-slave position convergence, especially under the influence of time-varying communication delays. This document presents an adaptive neural network compensation strategy within a proportional-derivative-like (P+d) control framework. The proposed controller addresses uncertainties associated with time delays and system dynamics using online adaptation of neural networks. Furthermore, a rigorous theoretical analysis of the closed-loop teleoperation system is presented and validated through numerical simulations on two-degree-of-freedom manipulators. Finally, the results demonstrate that adaptive neural networks can significantly improve the operational reliability of bilateral teleoperation systems in dynamic environments.

Source: IEEE Access

DOI: 10.1109/access.2025.3558119

Authors: Marco Moran-Armenta, Kleber Patiño, Emanuel Slawiñski, Francisco G. Rossomando, Vicente Mut, Javier Moreno-Valenzuela

Institutions: Instituto Politécnico Nacional, National University of San Juan

Language: English

Topic: Teleoperation and Haptic Systems

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,075

Funder: Secretaría de Investigación y Posgrado, Instituto Politécnico Nacional