Farajvand, Mahiyeh, García-Violini, Demián, Windt, Christian, Grazioso, Valerio and Ringwood, John (2021) Quantifying hydrodynamic model uncertainty for robust control of wave energy devices. In: 14th European Wave and Tidal Energy Conference, 5-9th Sept 2021, Plymouth, UK.
Preview
C402EW21MF.pdf
Download (2MB) | Preview
Abstract
Wave energy converter (WEC) modelling attracts significant uncertainty, often due to the need to
develop compact parametric models for simulation, optimisation and control design. For linear models, which
form the basis of many WEC control philosophies, this
uncertainty can be as a result of real system nonlinearity, particularly as a result of control action, as well as
more general uncertainty in the hydrodynamic modelling
process. Recent developments in WEC control include the
development of robust control algorithms, which utilise a
nominal linear model, but tolerate a level of uncertainty in
the model parameters. This study develops a framework
for identifying a nominal model plus model uncertainty
bounds, which uses data from nonlinear computational
fluid dynamics (CFD) simulation. Two robust control solutions are developed, one with an analytical approach, for
circular uncertainty boundaries, and a further numerical
approach, considering uncertainty sets of arbitrary shape.
Finally, the comparative controller performance, based on
the appropriate selection of a nominal model and uncertainty bound, compared to a non-robust nominal controller,
is shown.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Keywords: | Computational fluid dynamics; system identification; model uncertainty; pseudospectral; robust control; energy maximisation; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research |
Item ID: | 16256 |
Depositing User: | Professor John Ringwood |
Date Deposited: | 06 Jul 2022 09:06 |
Refereed: | Yes |
URI: | https://mu.eprints-hosting.org/id/eprint/16256 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
Downloads
Downloads per month over past year