Chattering in Sliding Mode Control of Robotic Manipulators

Many Sliding Mode Control (SMC) algorithms are developed and tested on robotic manipulators based on the premise that finite-time convergence can be achieved in practical systems. However, this idealistic approach only works theoretically, as parasitic dynamics (unmodeled dynamics) in real systems lead to non-vanishing oscillations instead of convergence to an equilibrium point. In this work, we argue this fundamental point for the case of robotic manipulators. Two SMC techniques—conventional and Terminal SMC—are analyzed using Describing Function analysis and the Locus of Perturbed Relay Systems on a SOPDT model and a two-link manipulator. Findings confirm that chattering, caused by parasitic dynamics, challenges the feasibility of SMC’s finite-time convergence in real-world applications.

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Publication Details

Published
2025-06-24
DOI
https://doi.org/10.23919/ecc65951.2025.11187270
Primary Topic
Robot Manipulation and Learning
Type
article
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article

Chattering in Sliding Mode Control of Robotic Manipulators

Igor Boiko, Yahya Zweiri, Ahmed Rehan
Robot Manipulation and Learning
article

Chattering in Sliding Mode Control of Robotic Manipulators

Igor Boiko, Yahya Zweiri, Ahmed Rehan
article en

Abstract

Many Sliding Mode Control (SMC) algorithms are developed and tested on robotic manipulators based on the premise that finite-time convergence can be achieved in practical systems. However, this idealistic approach only works theoretically, as parasitic dynamics (unmodeled dynamics) in real systems lead to non-vanishing oscillations instead of convergence to an equilibrium point. In this work, we argue this fundamental point for the case of robotic manipulators. Two SMC techniques—conventional and Terminal SMC—are analyzed using Describing Function analysis and the Locus of Perturbed Relay Systems on a SOPDT model and a two-link manipulator. Findings confirm that chattering, caused by parasitic dynamics, challenges the feasibility of SMC’s finite-time convergence in real-world applications.

Khalifa University of Science and Technology (AE)
Openalex Percentile: Top 63%
Robot Manipulation and Learning
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