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Addressing Control Implementation Issues in Robotic Systems Using Adaptive Control

Published online by Cambridge University Press:  14 May 2019

Rameez Hayat Open the ORCID record for Rameez Hayat [Opens in a new window] ,
Marion Leibold  and
Martin Buss
Rameez Hayat*
Affiliation:
Chair of Automatic Control Engineering, Department of Electrical and Computer Engineering, Technical University of Munich, Theresienstr. 90, 80333, Munich, Germany E-mail: marion.leibold@tum.de TUM Institute of Advanced Study, Technical University of Munich, Lichtenbergstrasse 2a, 85748 Garching, Germany E-mail: mb@tum.de
Marion Leibold
Affiliation:
Chair of Automatic Control Engineering, Department of Electrical and Computer Engineering, Technical University of Munich, Theresienstr. 90, 80333, Munich, Germany E-mail: marion.leibold@tum.de
Martin Buss
Affiliation:
Chair of Automatic Control Engineering, Department of Electrical and Computer Engineering, Technical University of Munich, Theresienstr. 90, 80333, Munich, Germany E-mail: marion.leibold@tum.de TUM Institute of Advanced Study, Technical University of Munich, Lichtenbergstrasse 2a, 85748 Garching, Germany E-mail: mb@tum.de
*
*Corresponding author. E-mail: rameez.hayat@tum.de
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Summary

This paper addresses three control implementation issues for trajectory tracking of robotic manipulators: unmodeled dynamics, unknown input saturation and peaking effects during the transient phase. A model-free first-order robust-adaptive control method is used to deal with the unmodeled dynamics. Robust optimality and stability of the controller are proved using the 𝓗∞ technique and the game-algebraic Riccati equation. An intuitive approach is devised to incorporate the unknown input saturation by modifying the speed of the desired trajectory. The trajectory scaling is performed by using only the state errors. Furthermore, two different techniques are utilized to suppress peaking during the transient response of the trajectory tracking. The first method adds an extra term in the input while the second method uses variable gain to improve the transient response. A systematic procedure for finding the controller parameters is formulated using features, such as rise time and settling time. A three-degree-of-freedom robot manipulator is used for the validation of the proposed controller in simulations and experiments.

Keywords

𝓗∞ optimal controlInput-to-state stabilityAdaptive controlOrbital stabilityComputed torqueEuler–Lagrange
Type
Articles
Information
Robotica , Volume 38 , Issue 1 , January 2020 , pp. 171 - 184
Copyright
© Cambridge University Press 2019 

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