An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point Absorbers
This article presents an intelligent fuzzy logic controller (FLC) for controlling single-body heaving wave energy converter (WEC) or what is widely known as “Point Absorber”. The controller aims at maximizing the energy captured from the sea waves. The power take-off (PTO) limitations are addressed...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2014-06-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/7/6/4033 |
| _version_ | 1798006289912037376 |
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| author | Mohammed Jama Addy Wahyudie Ali Assi Hassan Noura |
| author_facet | Mohammed Jama Addy Wahyudie Ali Assi Hassan Noura |
| author_sort | Mohammed Jama |
| collection | DOAJ |
| description | This article presents an intelligent fuzzy logic controller (FLC) for controlling single-body heaving wave energy converter (WEC) or what is widely known as “Point Absorber”. The controller aims at maximizing the energy captured from the sea waves. The power take-off (PTO) limitations are addressed implicitly in the fuzzy inference system (FIS) framework. In order to enhance the WEC power capturing bandwidth and make it less susceptible to wave environment irregularities and the system parametric uncertainties, the controller is built to have a self-configurable capability. This also eliminates the need to repeatedly run in-situ tuning procedure of the fuzzy controller or switch between several controllers based on the operating conditions. The fuzzy membership functions (MFs) are optimally tuned using particle swarm optimization (PSO) algorithm. To alleviate the computational burden associated with performing on-line optimization, the fuzzy controller is tuned at a rate significantly lower than the system sampling time. The suggested PSO-FLC has shown promising results compared with the fixed structure fuzzy logic controller (FS-FLC) and other passive control strategies. Several computer simulations were carried out to evaluate the controller effectiveness by applying different sea-states and analyzing the resultant WEC dynamics. |
| first_indexed | 2024-04-11T12:52:23Z |
| format | Article |
| id | doaj.art-f5f08c91dad64045a2cf7919175e5fec |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T12:52:23Z |
| publishDate | 2014-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-f5f08c91dad64045a2cf7919175e5fec2022-12-22T04:23:10ZengMDPI AGEnergies1996-10732014-06-01764033405310.3390/en7064033en7064033An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point AbsorbersMohammed Jama0Addy Wahyudie1Ali Assi2Hassan Noura3Electrical Engineering Department, United Arab Emirates University, Al Ain, P.O. Box 15551, UAEElectrical Engineering Department, United Arab Emirates University, Al Ain, P.O. Box 15551, UAEDepartment of Electrical and Electronics Engineering, Lebanese International University, Beirut, P.O. Box 146404, LebanonElectrical Engineering Department, United Arab Emirates University, Al Ain, P.O. Box 15551, UAEThis article presents an intelligent fuzzy logic controller (FLC) for controlling single-body heaving wave energy converter (WEC) or what is widely known as “Point Absorber”. The controller aims at maximizing the energy captured from the sea waves. The power take-off (PTO) limitations are addressed implicitly in the fuzzy inference system (FIS) framework. In order to enhance the WEC power capturing bandwidth and make it less susceptible to wave environment irregularities and the system parametric uncertainties, the controller is built to have a self-configurable capability. This also eliminates the need to repeatedly run in-situ tuning procedure of the fuzzy controller or switch between several controllers based on the operating conditions. The fuzzy membership functions (MFs) are optimally tuned using particle swarm optimization (PSO) algorithm. To alleviate the computational burden associated with performing on-line optimization, the fuzzy controller is tuned at a rate significantly lower than the system sampling time. The suggested PSO-FLC has shown promising results compared with the fixed structure fuzzy logic controller (FS-FLC) and other passive control strategies. Several computer simulations were carried out to evaluate the controller effectiveness by applying different sea-states and analyzing the resultant WEC dynamics.http://www.mdpi.com/1996-1073/7/6/4033wave energyfuzzy logicpower take-offparticle swarm optimization |
| spellingShingle | Mohammed Jama Addy Wahyudie Ali Assi Hassan Noura An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point Absorbers Energies wave energy fuzzy logic power take-off particle swarm optimization |
| title | An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point Absorbers |
| title_full | An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point Absorbers |
| title_fullStr | An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point Absorbers |
| title_full_unstemmed | An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point Absorbers |
| title_short | An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point Absorbers |
| title_sort | intelligent fuzzy logic controller for maximum power capture of point absorbers |
| topic | wave energy fuzzy logic power take-off particle swarm optimization |
| url | http://www.mdpi.com/1996-1073/7/6/4033 |
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