Data-Based Control of a Free-Free Beam in the Presence of Uncertainty
Conference paper (preprint)
WYOMING UNIV LARAMIE COLL OF ENGINEERING
Pagination or Media Count:
Linear control development is typically based on deterministic models that approximate the system under consideration. This approach neglects uncertainty in the system response. System uncertainty can arise from a number of sources including disturbances, noise, unmodeled dynamics, and nonlinearity. This may result in a reduction in performance or even instability in the closed loop system. The goal of this research is to account for measured uncertainty in control design. Our approach is to tune a baseline controller using a cost function that balances performance and robustness given measured system uncertainty. The approach is demonstrated on a free-free beam, with the goal of mitigating the flexural vibration. A lumped mass model is tuned to match the experimentally measured Frequency Response Function FRF of an experimental beam. This evaluation model and a reduced order model are used to approximate the beam dynamics. The baseline LQG controller is designed around the reduced order model of the beam. This controller is tuned according to the proposed cost function using the FRF and postulated variance. The cost function includes closed loop performance and stability robustness metrics. The resulting baseline and tuned controllers are evaluated on lumped mass models consistent with the measured data and uncertainty.
- Operations Research