Position estimation and object collision detection of a tendon-driven actuator based on a polytopic observer synthesis

Benoit Huard 1, 2, * Mathieu Grossard 1 Sandrine Moreau 2, 3 Thierry Poinot 3, 2
* Corresponding author
1 DIASI - Département Intelligence Ambiante et Systèmes Interactifs
2 LIAS - Laboratoire d'Informatique et d'Automatique pour les Systèmes
3 LAII - Laboratoire d'Automatique et d'Informatique Industrielle
Abstract : This paper proposes a multi-model based approach that estimates joint position and collision detection of a lightweight electric actuator dedicated to manipulation tasks. Taking advantage of an optimized back-drivable mechatronic design, the use of proprioceptive measures at the motor level enables the estimation of the unmeasured terminal position of the mechanical motor-to-joint transmission and force contact disturbance. A polytopic formulation is introduced based on an accurate model of the mechatronic transmission. Then, a multi-model observer-based estimator is synthesized using root-clustering for exteroceptive variables estimation without additional position/force sensor. The approach is experimentally validated with a single degree-of-freedom manipulator.
Keywords : Back-drivable actuator Least-squares identification Polytopic convex transformation Multi-model observer Linear matrix inequalities Collision detection
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Journal articles
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https://hal-cea.archives-ouvertes.fr/cea-01778155
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Submitted on : Wednesday, April 25, 2018 - 2:33:03 PM
Last modification on : Tuesday, January 7, 2020 - 9:04:02 AM

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Benoit Huard, Mathieu Grossard, Sandrine Moreau, Thierry Poinot. Position estimation and object collision detection of a tendon-driven actuator based on a polytopic observer synthesis. Control Engineering Practice, Elsevier, 2013, 21, pp.1178 - 1187. ⟨10.1016/j.conengprac.2013.04.008⟩. ⟨cea-01778155⟩

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