Robust control of a silicone soft robot using neural networks

Zheng, Gang; Zhou, Yuan; Ju, Mingda

Type de document :

Article dans une revue scientifique: Article original

DOI :

10.1016/j.isatra.2019.12.004

Titre :

Robust control of a silicone soft robot using neural networks

Auteur(s) :

Zheng, Gang [Auteur]

Deformable Robots Simulation Team [DEFROST ]
Zhou, Yuan [Auteur]
Shanghai Jiao Tong University [Shanghai]
Ju, Mingda [Auteur]
Equipes Traitement de l'Information et Systèmes [ETIS - UMR 8051]

Titre de la revue :

ISA Transactions

Pagination :

38-45

Éditeur :

Elsevier

Date de publication :

2020-05

ISSN :

0019-0578

Mot(s)-clé(s) en anglais :

Soft robot
Machine Learning
Robust control

Discipline(s) HAL :

Informatique [cs]/Robotique [cs.RO]

Résumé en anglais : [en]

This paper deals with the robust controller design problem to regulate the position of a soft robot with elastic behavior, driven by 4 cable actuators. In this work, we first used an artificial neural network to approximate ...
Lire la suite >This paper deals with the robust controller design problem to regulate the position of a soft robot with elastic behavior, driven by 4 cable actuators. In this work, we first used an artificial neural network to approximate the relation between these actuators and the controlled position of the soft robot, based on which two types of robust controllers (type of integral and sliding mode) are proposed. The effectiveness and the robustness of the proposed controllers have been analyzed both for the constant and the time-varying disturbances. The performances (precision, convergence speed and robustness) of the proposed method have been validated via different experimental tests.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

ULNE

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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