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On the Combined Inverse-Dynamics/Passivity-Based Control of Elastic-Joint Robots

Andrea Giusti, Jörn Malzahn, Matthias Althoff

Year
2018
Citations
32

Abstract

In this paper, we present a novel global tracking control approach for elastic-joint robots that can be efficiently computed and is robust against model uncertainties and input disturbances. Elastic-joint robots provide enhanced safety and resiliency for interaction with the environment and humans. On the other hand, the joint elasticity complicates the motion-control problem especially when robust and precise trajectory tracking is required. Our proposed control approach allows us to merge the main benefits of the two well-known control schemes: inverse-dynamics (ID) control, which can be efficiently computed thanks to modern recursive algorithms, and passivity-based (PB) tracking control, which provides enhanced robustness to model uncertainty and external disturbances. As an extension of our previous work, we present a detailed robustness analysis of our combined ID/PB controller, a new variant of the original scheme that shows practically relevant implications, and finally, experimental results that verify the effectiveness of the approach.

Keywords

Robustness (evolution)Inverse dynamicsControl theory (sociology)Computer sciencePassivityRobotMerge (version control)Robust controlMotion controlControl engineering

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