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 language | English |
|---|---|
| Title of host publication | 5th International Conference on Renewable Energy |
| Subtitle of host publication | Generation and Application, ICREGA 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 132-135 |
| Number of pages | 4 |
| Volume | 2018-January |
| ISBN (Electronic) | 9781538622513 |
| DOIs | |
| Publication status | Published - Apr 12 2018 |
| Event | 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018 - Al Ain, United Arab Emirates Duration: Feb 26 2018 → Feb 28 2018 |
Other
| Other | 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018 |
|---|---|
| Country/Territory | United Arab Emirates |
| City | Al Ain |
| Period | 2/26/18 → 2/28/18 |
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
