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A Robust Linear Control Strategy to Enhance Damping of a Series Elastic Actuator on a Collaborative Robot

  • S. GhidiniEmail author
  • M. Beschi
  • N. Pedrocchi
Article
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Abstract

Dealing with the physical interaction between humans and robots, Series Elastic Actuators (SEAs) are identified as one solution to overcome many limits, such as reducing contact forces or detect collisions. Nevertheless, the low-damping dynamic of a SEA can lead to undesired behaviours, especially during particular applications where a high level of precision is required. In this paper, a linear control architecture to enhance the damping performance of a SEA is presented. The proposed structure consists in a cascade control where loops are regulated using three types of controllers: PI, PD and a generalized controller specifically designed to damp oscillations. A frequency-domain approach with related constraints could not satisfy the time-domain goal in term of oscillation damping, for this reason an optimization problem able to consider them both is taken into account. A robust design is mandatory to the model mismatch introduced by neglecting coupling between motor. Therefore, robustness constraints are introduced in the optimization procedure. Indeed, the effectiveness of the control architecture is tested on a real compliant robot with six degrees of freedom equipped with as many SEAs. Each test aims to highlight the damping performance of the controlled system while the robot performs various tasks or it is subject to external disturbances.

Keywords

Collaborative robots Tuning rules Series elastic actuator Damped control Robust control 

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Notes

Acknowledgments

The work is partially supported by FourByThree Project H2020-FoF-06-2014-737095.

Compliance with Ethical Standards

Conflict of interests

None declared.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Institute of Intelligent Industrial Technologies and Systems for Advanced ManufacturingNational Research Council of ItalyMilanItaly

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