In this paper, a purely data-driven approach for force estimation in electro-mechanical actuators is proposed. First, the contact with the surrounding environment is detected by means of an unsupervised learning procedure applied to the current measurements, then the clamping force is estimated in real-time by using a data-driven model of the interaction between the actuator and the system. The effectiveness of the proposed approach is illustrated on an experimental braking system setup, also showing to outperform the state of the art methodology.

Force estimation in electro-mechanical systems: theory and experiments

Riva G.;Formentin S.;Savaresi S. M.
2021

Abstract

In this paper, a purely data-driven approach for force estimation in electro-mechanical actuators is proposed. First, the contact with the surrounding environment is detected by means of an unsupervised learning procedure applied to the current measurements, then the clamping force is estimated in real-time by using a data-driven model of the interaction between the actuator and the system. The effectiveness of the proposed approach is illustrated on an experimental braking system setup, also showing to outperform the state of the art methodology.
CCTA 2021 - 5th IEEE Conference on Control Technology and Applications
978-1-6654-3643-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1209179
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