A comparative analysis of linear and nonlinear control of wave energy converter for a force control application
Journal article, 2019

The aim of wave energy converters (WECs) is to harvest the energy from the ocean waves and convert into electricity. Optimizing the generator output is a vital point of research. A WEC behaves as a nonlinear system in real ocean waves and a control that approximates the behaviour of the system is required. In order to predict the behaviour of WEC, a controller is implemented with an aim to track the referenced trajectory for a force control application of the WEC. A neural model is implemented for the system identification and control of the nonlinear process with a neural nonlinear autoregressive moving average exogenous (NARMAX) model. The neural model updates the weights to reduce the error by using the Levenberg-Marquardt back-propagation algorithm for a single-input-single-output (SISO) nonlinear system. The performance of the system under the proposed scheme is compared to the same system under a PI-controller scheme, where the PI gains have been tuned accordingly, to verify the control capacity of the proposed controller. The results show a good tracking of dq (direct-quadrature) axes currents by regulating the stator currents, and hence a force control is achieved at different positions of the translator. The dynamic performance of the control is verified in a time domain analysis for the displacement of the translator.

Permanent magnet linear generator (PMLG)

Neural NARMAX

Current control

Force control

Wave energy converter

Author

Arvind Parwal

Uppsala University

Martin Fregelius

Uppsala University

P. M. Almeida

Federal University of Juiz de Fora

Olle Svensson

Uppsala University

Irina Temiz

Uppsala University

Janaina G.de Oliveira

Federal University of Juiz de Fora

Cecilia Boström

Uppsala University

Mats Leijon

Chalmers, Electrical Engineering, Electric Power Engineering

Uppsala University

International Marine Energy Journal

26315548 (eISSN)

Vol. 2 1 39-50

Subject Categories

Control Engineering

Signal Processing

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.36688/imej.2.39-50

More information

Latest update

3/22/2021