Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy Framework
The article portrays an adaptive control paradigm for the swift response of a solid-oxide fuel cell (SOFC) in a grid-connected microgrid. The control scheme is based on an adaptive feedback-linearization-embedded fully recurrent NeuroFuzzy Laguerre wavelet control (FBL-FRNF-Lag-WC) framework. The no...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/14/7/1850 |
| _version_ | 1797539927965040640 |
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| author | Muhammad Awais Laiq Khan Saghir Ahmad Mohsin Jamil |
| author_facet | Muhammad Awais Laiq Khan Saghir Ahmad Mohsin Jamil |
| author_sort | Muhammad Awais |
| collection | DOAJ |
| description | The article portrays an adaptive control paradigm for the swift response of a solid-oxide fuel cell (SOFC) in a grid-connected microgrid. The control scheme is based on an adaptive feedback-linearization-embedded fully recurrent NeuroFuzzy Laguerre wavelet control (FBL-FRNF-Lag-WC) framework. The nonlinear functions of feedback linearization (FBL) are estimated using a fully recurrent NeuroFuzzy Laguerre wavelet control (FRNF-Lag-WC) architecture with a recurrent Gaussian membership function in the antecedent part and a recurrent Laguerre wavelet in the consequent part, respectively. The performance of the proposed control scheme is validated for various stability, quality, and reliability factors obtained through a simulation testbed implemented in MATLAB/Simulink. The proposed scheme is compared against adaptive NeuroFuzzy, PID, and adaptive PID (aPID) control schemes using different performance parameters for a grid-connected load over 24 h. |
| first_indexed | 2024-03-10T12:52:47Z |
| format | Article |
| id | doaj.art-f7899e091a9546d5b97424bfafc27efe |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T12:52:47Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-f7899e091a9546d5b97424bfafc27efe2023-11-21T12:58:50ZengMDPI AGEnergies1996-10732021-03-01147185010.3390/en14071850Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy FrameworkMuhammad Awais0Laiq Khan1Saghir Ahmad2Mohsin Jamil3Department of Electrical and Computer Engineering, COMSATS University Islamabad-Abbottabad Campus, Abbottabad 22060, PakistanDepartment of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, PakistanDepartment of Electrical and Computer Engineering, COMSATS University Islamabad-Abbottabad Campus, Abbottabad 22060, PakistanDepartment of Electrical and Computer Engineering, Faculty of Engineering and Applied Sciences, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, CanadaThe article portrays an adaptive control paradigm for the swift response of a solid-oxide fuel cell (SOFC) in a grid-connected microgrid. The control scheme is based on an adaptive feedback-linearization-embedded fully recurrent NeuroFuzzy Laguerre wavelet control (FBL-FRNF-Lag-WC) framework. The nonlinear functions of feedback linearization (FBL) are estimated using a fully recurrent NeuroFuzzy Laguerre wavelet control (FRNF-Lag-WC) architecture with a recurrent Gaussian membership function in the antecedent part and a recurrent Laguerre wavelet in the consequent part, respectively. The performance of the proposed control scheme is validated for various stability, quality, and reliability factors obtained through a simulation testbed implemented in MATLAB/Simulink. The proposed scheme is compared against adaptive NeuroFuzzy, PID, and adaptive PID (aPID) control schemes using different performance parameters for a grid-connected load over 24 h.https://www.mdpi.com/1996-1073/14/7/1850SOFCmicrogridfeedback linearizationLaguerre waveletrecurrent NeuroFuzzyhybrid power system |
| spellingShingle | Muhammad Awais Laiq Khan Saghir Ahmad Mohsin Jamil Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy Framework Energies SOFC microgrid feedback linearization Laguerre wavelet recurrent NeuroFuzzy hybrid power system |
| title | Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy Framework |
| title_full | Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy Framework |
| title_fullStr | Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy Framework |
| title_full_unstemmed | Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy Framework |
| title_short | Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy Framework |
| title_sort | feedback linearization based fuel cell adaptive control paradigm in a microgrid using a wavelet entrenched neurofuzzy framework |
| topic | SOFC microgrid feedback linearization Laguerre wavelet recurrent NeuroFuzzy hybrid power system |
| url | https://www.mdpi.com/1996-1073/14/7/1850 |
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