A significant challenge associated with the development of precision motion control systems is the identification and modeling of friction. In particular, dynamic (presliding) friction is often difficult to accurately model in both the time domain and frequency domain simultaneously. We present a data-based modification to an existing friction model, known as the Dahl Dynamic Hysteresis Model (DHM), which incorporates an empirical friction slope function to provide a more accurate representation of arbitrarily shaped hysteresis curves. This data-based approach avoids the added complexity of identifying or fitting model parameters, and can be implemented with a simple look up table. Simulation results are validated with measured friction data collected from an experimental testbed. We show that the data-based approach significantly improves the friction model accuracy in both the time and frequency domains.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5829-5
PROCEEDINGS PAPER
An Improved Dynamic Friction Model Using a Data-Based Approach
Nathan A. Weir,
Nathan A. Weir
University of Illinois at Urbana-Champaign, Urbana, IL
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Andrew G. Alleyne
Andrew G. Alleyne
University of Illinois at Urbana-Champaign, Urbana, IL
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Nathan A. Weir
University of Illinois at Urbana-Champaign, Urbana, IL
Andrew G. Alleyne
University of Illinois at Urbana-Champaign, Urbana, IL
Paper No:
DSCC2017-5225, V003T27A009; 7 pages
Published Online:
November 14, 2017
Citation
Weir, NA, & Alleyne, AG. "An Improved Dynamic Friction Model Using a Data-Based Approach." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 3: Vibration in Mechanical Systems; Modeling and Validation; Dynamic Systems and Control Education; Vibrations and Control of Systems; Modeling and Estimation for Vehicle Safety and Integrity; Modeling and Control of IC Engines and Aftertreatment Systems; Unmanned Aerial Vehicles (UAVs) and Their Applications; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Control of Smart Buildings and Microgrids; Energy Systems. Tysons, Virginia, USA. October 11–13, 2017. V003T27A009. ASME. https://doi.org/10.1115/DSCC2017-5225
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