Maximising absorbed energy using neuro-adaptive controller for heaving point absorbers

Muhammad Saleheen Aftab, Addy Wahyudie

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

1 Citation (Scopus)

Abstract

This paper presents a computation-friendly control approach to improve extracted power from sea waves with heaving wave energy converter. A Lyponov function based neuro-adaptive inverse controller is proposed for velocity tracking of the heaving buoy under resonance condition for maximum power transfer. The reference velocity is generated offline by optimizing the absorbed energy with constraints on buoy's excursion. Analysis of simulation study validates a superior velocity tracking along with enhanced power capture from the proposed scheme as compared to passive loading technique in irregular sea conditions.

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.
Pages124-127
Number of pages4
Volume2018-January
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

Other

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

Keywords

  • artificial neural network
  • heaving point absorber
  • Lyaponuv stability theory
  • wave energy converter

ASJC Scopus subject areas

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

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