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Control force limitation in wave energy converter using neuro-adaptive hierarchical control scheme

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

Abstract

In this paper, a simple hierarchical control strategy is presented for heaving wave energy converters. The low level control is implemented with a Lyapunov function neuro-adaptive controller, whereas for the high level control a fast iterative algorithm is utilized to generate the velocity reference for the low level controller. Simulation studies conducted for moderate sea-state exhibit an efficient velocity tracking and power capture. In comparison to the resistive loading technique, the achieved results indeed confirm an overall superior performance of the presented scheme.

Original languageEnglish
Title of host publication5th International Conference on Renewable Energy
Subtitle of host publicationGeneration and Application, ICREGA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages132-135
Number of pages4
ISBN (Electronic)9781538622513
DOIs
Publication statusPublished - Apr 12 2018
Event5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018 - Al Ain, United Arab Emirates
Duration: Feb 26 2018Feb 28 2018

Publication series

Name5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018
Volume2018-January

Other

Other5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018
Country/TerritoryUnited Arab Emirates
CityAl Ain
Period2/26/182/28/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • artificial neural network
  • hierarchical control strategy
  • high level control
  • low level control
  • wave energy converter

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

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