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Uncertainty Bounding of CFRP Beams Towards Robust Control of Flexible Composite Structures

[+] Author Affiliations
Alexander H. Pesch, Tamunomiesiya LongJohn, Kristopher Wagner, Brian J. McAndrews

Hofstra University, Hempstead, NY

Paper No. DSCC2017-5258, pp. V002T05A004; 8 pages
  • ASME 2017 Dynamic Systems and Control Conference
  • Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications
  • Tysons, Virginia, USA, October 11–13, 2017
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5828-8
  • Copyright © 2017 by ASME


As composite materials are becoming increasingly applied in actively controlled flexible structures, the need for practical uncertainty bounding to capture the effect of normal manufacturing variations on their dynamic behavior is also increasing. Currently, there is a lack of quantification of manufacturing variation of composite materials cast in a robust control framework. This work presents a simple experimental study on a particular case of composite member. The modal parameters of a set of 12 unidirectional carbon fiber reinforce polymer beams are identified. A nominal finite element model is numerically fit to the average experimental natural frequencies and antiresonances. The model is augmented with real parametric uncertainties placed on the modal parameters. The bound on the uncertainties is found both deterministically, to capture all experimentally observed data, and stochastically using a predetermined confidence interval. The two uncertainty bounding approaches are compared through the resulting bound on the beam model frequency response. Also, simulations are conducted to compare possible time responses using the two uncertainty bounds. It is found that the utilized structure of parametric uncertainties is effective at capturing the experimentally observed behavior.

Copyright © 2017 by ASME



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