Bacelli, Giorgio and Ringwood, John (2015) Numerical Optimal Control of Wave Energy Converters. IEEE Transactions on Sustainable Energy, 6 (2). pp. 294-302. ISSN 1949-3029
Preview
JR-Numerical-2015.pdf
Download (898kB) | Preview
Abstract
Energy maximizing control for wave energy converters (WECs) is a nonstandard optimal control problem. While the constrained optimal control problem for WECs has been addressed by model-predictive control strategies, such strategies need to employ cost function modifications due to convexity problems and the algorithms are computationally complex, making real-time implementation difficult. The recently developed family of direct transcription methods offer a promising alternative, since they are computationally efficient and a convex problem results. Moreover, constraints on both the device displacement and velocity, and power take off force, are easily incorporated. Both single-body and multibody device models can be used, as well as arrays of single-body or multibody devices.
Item Type: | Article |
---|---|
Additional Information: | This work was supported in part by Enterprise Ireland under Grant EI/TD/2009/0331. |
Keywords: | Control systems; direct transcription; wave energy; |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > Centre for Ocean Energy Research Faculty of Science and Engineering > Electronic Engineering |
Item ID: | 9435 |
Identification Number: | 10.1109/TSTE.2014.2371536 |
Depositing User: | Professor John Ringwood |
Date Deposited: | 01 May 2018 15:28 |
Journal or Publication Title: | IEEE Transactions on Sustainable Energy |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Funders: | Enterprise Ireland (EI) |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/9435 |
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