Estimation of incident wave of AWS-based wave energy converter using extended Kalman filter

Jae Seung Kim, Jung Yoon Kim, Jin Bae Park

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

1 Citation (Scopus)

Abstract

This paper presents a novel method of estimating ocean waves by measuring current outputs from the Archimedes Wave Swing (AWS) wave energy converter (WEC). The wave period and height are crucial information to maximize the power output from the AWS. However, since the AWS is installed on the seabed, additional sensors and buoys are required to obtain the ocean wave information. The extended Kalman filter (EKF) is applied to obtain the states of the ocean wave by measuring the generator current in the α - β domain. As the EKF requires the Jacobian matrix of the system dynamic equations for the system matrix, simplified hydrodynamics of the floater including the Froude-Krylov excitation force and the domain α - β voltage equation of the generator is derived to develop the mathematical model of the AWS. In order to verify the performance of the estimator, a numerical simulation is performed and presented and it shows great agreement with the actual motion.

Original languageEnglish
Title of host publicationICCAS 2013 - 2013 13th International Conference on Control, Automation and Systems
Pages1411-1416
Number of pages6
DOIs
Publication statusPublished - 2013
Event2013 13th International Conference on Control, Automation and Systems, ICCAS 2013 - Gwangju, Korea, Republic of
Duration: 2013 Oct 202013 Oct 23

Publication series

NameInternational Conference on Control, Automation and Systems
ISSN (Print)1598-7833

Other

Other2013 13th International Conference on Control, Automation and Systems, ICCAS 2013
Country/TerritoryKorea, Republic of
CityGwangju
Period13/10/2013/10/23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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