Hybrid moment/position control of a parallel robot View Full Text


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Article Info

DATE

2012-06-13

AUTHORS

Mohamed El Hossine Daachi, Brahim Achili, Boubaker Daachi, Yacine Amirat, Djamel Chikouche

ABSTRACT

In this paper, a hybrid moment/position controller in task space is proposed for tasks involving a contact between a robot and its environment. We consider a contour-tracking task performed by a six DOF (Degrees Of Freedom) parallel robot. The task space dynamic model of the robot in contact with its environment, seen as a black box, is estimated by a MLP-NN (MultiLayer Perceptron Neural Network). The neural network non-linearity is treated using Taylor series expansion. An adaptation algorithm of the neural parameters resulting from a closed-loop stability analysis is proposed. The performance of the proposed controller is validated on the C5 parallel robot by considering two different environments: rigid and compliant. More... »

PAGES

536-546

References to SciGraph publications

  • 2011-06-01. Neural network based hybrid force/position control for robot manipulators in INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING
  • 2010-04-16. A C5 parallel robot identification and control in INTERNATIONAL JOURNAL OF CONTROL, AUTOMATION AND SYSTEMS
  • 2006-07. A Neural Network Adaptive Controller for End-effector Tracking of Redundant Robot Manipulators in JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
  • 1999-03. Neural Network Force Control for Industrial Robots in JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12555-012-0310-z

    DOI

    http://dx.doi.org/10.1007/s12555-012-0310-z

    DIMENSIONS

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