Unscented Kalman filtering for wave energy converters system identification

Mohd Aftar Abu Bakar, David A. Green, Andrew V. Metcalfe, Noratiqah Mohd Ariff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A model for a oscillating flap wave energy converter (WEC) is as a single degree of freedom system with a non-linear term to allow for the drag of the device through the water, known as the Morison term. The focus of this system identification is on estimating the dynamic state of the system and estimating the non-linear parameter from observations of the wave elevation and the vertical displacement of the device. It is assumed that the mass, stiffness and damping of the system, without the Morison term, are known from the physical characteristics of the device. The Kalman Filter (KF) can be used to estimate the states of a linear system, however, it is not directly applicable to a non-linear system. Various adaptations have been proposed for non-linear systems. One of the first was the extended Kalman Filter (EKF) which relied on a linearization about the current state values. However, an alternative approach, known as the unscented Kalman Filter (UKF) has been found to give a better performance and is easier to implement. We apply the UKF to estimate the dynamic states of the system together with the non-linear parameter. The fitted model can be used to predict the performance of the device in different wave environments.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
PublisherAmerican Institute of Physics Inc.
Pages304-310
Number of pages7
Volume1602
ISBN (Print)9780735412361
DOIs
Publication statusPublished - 2014
Event3rd International Conference on Mathematical Sciences, ICMS 2013 - Kuala Lumpur
Duration: 17 Dec 201319 Dec 2013

Other

Other3rd International Conference on Mathematical Sciences, ICMS 2013
CityKuala Lumpur
Period17/12/1319/12/13

Fingerprint

direct power generators
system identification
Kalman filters
nonlinear systems
estimating
linearization
estimates
linear systems
drag
stiffness
degrees of freedom
damping
water

Keywords

  • System identification
  • Unscented kalman filter
  • Wave energy converters

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Abu Bakar, M. A., Green, D. A., Metcalfe, A. V., & Mohd Ariff, N. (2014). Unscented Kalman filtering for wave energy converters system identification. In AIP Conference Proceedings (Vol. 1602, pp. 304-310). American Institute of Physics Inc.. https://doi.org/10.1063/1.4882503

Unscented Kalman filtering for wave energy converters system identification. / Abu Bakar, Mohd Aftar; Green, David A.; Metcalfe, Andrew V.; Mohd Ariff, Noratiqah.

AIP Conference Proceedings. Vol. 1602 American Institute of Physics Inc., 2014. p. 304-310.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abu Bakar, MA, Green, DA, Metcalfe, AV & Mohd Ariff, N 2014, Unscented Kalman filtering for wave energy converters system identification. in AIP Conference Proceedings. vol. 1602, American Institute of Physics Inc., pp. 304-310, 3rd International Conference on Mathematical Sciences, ICMS 2013, Kuala Lumpur, 17/12/13. https://doi.org/10.1063/1.4882503
Abu Bakar MA, Green DA, Metcalfe AV, Mohd Ariff N. Unscented Kalman filtering for wave energy converters system identification. In AIP Conference Proceedings. Vol. 1602. American Institute of Physics Inc. 2014. p. 304-310 https://doi.org/10.1063/1.4882503
Abu Bakar, Mohd Aftar ; Green, David A. ; Metcalfe, Andrew V. ; Mohd Ariff, Noratiqah. / Unscented Kalman filtering for wave energy converters system identification. AIP Conference Proceedings. Vol. 1602 American Institute of Physics Inc., 2014. pp. 304-310
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