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Model Predictive Controller for a Planar Tensegrity Mechanism with decoupled position and stiffness control

Jurado Realpe 1 Salih Abdelaziz 1 Philippe Poignet 1
1 DEXTER - Conception et commande de robots pour la manipulation
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Precise trajectory tracking and stiffness modulation for tensegrity mechanisms are a challenging topic that can open new horizon of applications for this type of systems. This paper presents a new control strategy of tensegrity mechanisms using a model predictive controller (MPC). Based on a dynamic model, the proposed approach allows to track trajectories with low and relatively high dynamics as well as to modulate the mechanism stiffness by changing only the controller's parameters. Trajectories of 30s, 5s and 1s are performed showing a trajectory tracking improvement of up to 64% in the root mean square error when compared to literature results.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-03140520
Contributor : Salih Abdelaziz <>
Submitted on : Friday, February 12, 2021 - 10:41:05 PM
Last modification on : Tuesday, March 9, 2021 - 5:09:37 PM
Long-term archiving on: : Friday, May 14, 2021 - 9:34:32 AM

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Jurado Realpe, Salih Abdelaziz, Philippe Poignet. Model Predictive Controller for a Planar Tensegrity Mechanism with decoupled position and stiffness control. 17th International Symposium on Advances in Robot Kinematics (ARK 2020), Jun 2020, Ljubljana, Slovenia. pp.349-358, ⟨10.1007/978-3-030-50975-0_43⟩. ⟨lirmm-03140520⟩

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