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Observer-Based Unknown Input Estimator of Wave Excitation Force for a Wave Energy Converter

Abdelrahman, Mustafa; Patton, Ron

Authors

Mustafa Abdelrahman



Abstract

Several energy maximization control approaches for point-absorber wave-energy converter (PAWEC) systems require knowledge of the wave excitation force (WEF) that is not measurable during the PAWEC operation. Many WEF estimators have been proposed based on stochastic PAWEC modeling using the Kalman filter (KF), extended KF (EKF), or receding-horizon estimation. Alternatively, a deterministic WEF estimator is proposed here based on the fast unknown input estimation (FUIE) concept. The WEF is estimated as an unknown input obviating the requirement to represent its dynamics. The proposed observer-based unknown input estimator (OBUIE) inherits the capability of estimating fast-changing signals from the FUIE, which is important when considering irregular wave conditions. Unlike preceding methods, the OBUIE is designed based on a PAWEC model, including the nonlinear viscous drag force. It has been shown that the nonlinear viscous drag force is essential for accurate PAWEC model description, within the energy maximization control role. The performance of the proposed estimator is evaluated in terms of PAWEC conversion efficiency in a single degree-of-freedom PAWEC device operating in regular and irregular waves. Simulation results are obtained using MATLAB to evaluate the estimator under different control methods and subject to parametric uncertainty.

Journal Article Type Article
Journal IEEE Transactions on Control Systems Technology
Print ISSN 1063-6536
Electronic ISSN 1558-0865
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Pages 1-8
APA6 Citation Abdelrahman, M., & Patton, R. (in press). Observer-Based Unknown Input Estimator of Wave Excitation Force for a Wave Energy Converter. IEEE Transactions on Control Systems Technology, 1-8. https://doi.org/10.1109/tcst.2019.2944329
DOI https://doi.org/10.1109/tcst.2019.2944329
Keywords Control and Systems Engineering; Electrical and Electronic Engineering

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