Control of a compliant gripper via least-squares support vector regression (LS-SVR) with particle swarm optimization (PSO) algorithm

Control of a compliant gripper via least-squares support vector regression (LS-SVR) with particle swarm optimization (PSO) algorithm

This study focuses on controlling a compliant gripper using least-squares support vector regression (LS-SVR) combined with a particle swarm optimization (PSO) algorithm. The compliant gripper is designed to grip small objects with high precision. However, repeated use can lead to reduced precision d...

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Bibliographic Details
Main Authors: Poonnapa Chaichudchaval, Archawin Chaitrekal, Nawin Sutthiprapa, Dung-An Wang, Teeranoot Chanthasopeephan
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Systems Science & Control Engineering
Subjects:
Compliant gripper
hysteresis
least-squares support vector regression
particle swarm optimization
Online Access:https://www.tandfonline.com/doi/10.1080/21642583.2025.2518962
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