A spatiotemporal estimation framework for real-world LIDAR wind speed measurements

Mercieca, J. orcid.org/0000-0002-9351-3256, Aram, P. orcid.org/0000-0003-4223-2304, Jones, B.L. orcid.org/0000-0002-7465-1389 et al. (1 more author) (2020) A spatiotemporal estimation framework for real-world LIDAR wind speed measurements. IEEE Transactions on Control Systems Technology, 28 (4). pp. 1595-1602. ISSN 1063-6536

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: Differential-algebraic equations; light detection and ranging (LIDAR); Navier-Stokes equations; partial differential equations; unscented Kalman filter (UKF); wind turbines
Dates:
  • Accepted: 24 March 2019
  • Published (online): 8 May 2019
  • Published: July 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 23 May 2019 16:04
Last Modified: 03 Dec 2021 11:09
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: https://doi.org/10.1109/tcst.2019.2913134

Export

Statistics