Real-time model predictive control framework for a point absorber wave energy converter with excitation force estimation and prediction

Elamin, Abdin Y. and Wahyudie, Addy and Hashfi, Tuanku Badzlin and Shareef, Hussain and Errouissi, Rachid and Laghari, Mohammad Shakeel and Mubin, Marizan and Mekhilef, Saad (2024) Real-time model predictive control framework for a point absorber wave energy converter with excitation force estimation and prediction. IEEE Access, 12. pp. 4078-4098. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2023.3347731.

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Official URL: https://doi.org/10.1109/ACCESS.2023.3347731

Abstract

This study focuses on real-time model predictive control (MPC) implementation for a point-absorber-type wave energy converter (WEC) to achieve maximum wave power extraction. To address the MPC dependence on current and future wave excitation force knowledge, the control framework includes a square-root unscented Kalman filter (SR-UKF) to estimate the wave excitation force, whereas an autoregressive (AR) model forecasts the excitation force over the prediction horizon. The MPC utilizes a linear model of the point absorber, and its cost function is formulated as a quadratic programming (QP) problem with the objective of maximizing the wave energy extraction subject to physical limitations and constraints. A set of Laguerre functions was used to reduce the MPC computational complexity by decreasing the number of decision variables in the QP problem. The MATLAB/Simulink simulation results showed that the embodiment of point absorber nonlinearities by the SR-UKF enhanced the estimation accuracy compared with that of linear Kalman filters in terms of maximum error, root mean square error, and goodness of fit. Moreover, an AR model of order 100 provided satisfactory prediction performance for a 4 s prediction. The MPC strategy was simulated to evaluate its efficiency with respect to the absorbed wave power and generated electrical power under different sea-state conditions and disturbance uncertainties. Depending on sea state, it was found that the proposed MPC strategy generated 27.8% to 80% more electrical power than resistive loading control. Finally, a hardware-in-the-loop experimental setup was used to validate the computational viability of the proposed control framework in real-time WEC applications.

Item Type: Article
Funders: United Arab Emirates University (UAEU) Ph.D. Fund
Uncontrolled Keywords: Autoregressive model; hardware-in-the-loop; Kalman filter; model predictive control; permanent magnet linear generator; power maximization; wave energy converter
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Department of Electrical Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 20 Jun 2024 01:09
Last Modified: 20 Jun 2024 01:09
URI: http://eprints.um.edu.my/id/eprint/44194

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