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Comparison of two robust predictive control strategies for trajectory tracking of flexible-joint robots

Maria Makarov, Mathieu Grossard, Pedro Rodríguez-Ayerbe, D. Dumur

Year
2014
Citations
4

Abstract

Two control design approaches are proposed for robust and accurate trajectory tracking of flexible-joint robot manipulators using motor-side measurements only. Within a two-degrees-of-freedom linear controller structure with reference anticipation, the design methods are based either on the Generalized Predictive Control (GPC) or the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> frameworks. In the first case, the approach considers the Youla parametrization of an initial GPC controller, while in the second case, a two-degree-of-freedom H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller with anticipated reference is synthesized. Experimental evaluation of both methods is performed using the CEA lightweight ASSIST robot arm under rigid model-based compensation, which is modeled as an uncertain system and preliminary identified experimentally. Benefits and drawbacks of both methods are discussed.

Keywords

TrajectoryParametrization (atmospheric modeling)Controller (irrigation)RobotControl theory (sociology)Computer scienceCompensation (psychology)Model predictive controlTracking (education)Control engineering

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