Regular Papers

International Journal of Control, Automation and Systems 2012; 10(3): 536-546

Published online June 13, 2012

https://doi.org/10.1007/s12555-012-0310-z

© The International Journal of Control, Automation, and Systems

Hybrid Moment/Position Control of a Parallel Robot

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

University of Sétif, Algeria

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 al-gorithm of the neural parameters resulting from a closed-loop stability analysis is proposed. The per-formance of the proposed controller is validated on the C5 parallel robot by considering two different environments: rigid and compliant.

Keywords Adaptive control, MLP neural networks, parallel robot, stability analysis.

Article

Regular Papers

International Journal of Control, Automation and Systems 2012; 10(3): 536-546

Published online June 1, 2012 https://doi.org/10.1007/s12555-012-0310-z

Copyright © The International Journal of Control, Automation, and Systems.

Hybrid Moment/Position Control of a Parallel Robot

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

University of Sétif, Algeria

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 al-gorithm of the neural parameters resulting from a closed-loop stability analysis is proposed. The per-formance of the proposed controller is validated on the C5 parallel robot by considering two different environments: rigid and compliant.

Keywords: Adaptive control, MLP neural networks, parallel robot, stability analysis.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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