A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board

Photovoltaic (PV) inverters essentially convert DC quantities, such as voltage and current, to AC quantities whose magnitude and frequency are controlled to obtain the desired output. Thus, the performance of an inverter depends on its controller. Therefore, an optimum fuzzy logic controller (FLC) d...

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Main Authors: Ammar Hussein Mutlag, Azah Mohamed, Hussain Shareef
Format: Article
Language:English
Published: MDPI AG 2016-02-01
Series:Energies
Subjects:
Online Access:http://www.mdpi.com/1996-1073/9/3/120
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spelling doaj-75000b632c824f16adc9a2d7e68a58752020-11-24T22:58:21ZengMDPI AGEnergies1996-10732016-02-019312010.3390/en9030120en9030120A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 BoardAmmar Hussein Mutlag0Azah Mohamed1Hussain Shareef2Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, MalaysiaDepartment of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, MalaysiaDepartment of Electrical Engineering, United Arab Emirates University, 15551 Al-Ain, UAEPhotovoltaic (PV) inverters essentially convert DC quantities, such as voltage and current, to AC quantities whose magnitude and frequency are controlled to obtain the desired output. Thus, the performance of an inverter depends on its controller. Therefore, an optimum fuzzy logic controller (FLC) design technique for PV inverters using a lightning search algorithm (LSA) is presented in this study. In a conventional FLC, the procedure for obtaining membership functions (MFs) is usually implemented using trial and error, which does not lead to satisfactory solutions in many cases. Therefore, this study presents a technique for obtaining MFs that avoids the exhaustive traditional trial-and-error procedure. This technique is implemented during the inverter design phase by generating adaptive MFs based on the evaluation results of the objective function formulated with LSA. The mean squared error (MSE) of the inverter output voltage is used as an objective function in this study. LSA optimizes the MFs such that the inverter provides the lowest MSE for the output voltage, and the performance of the PV inverter output is improved in terms of amplitude and frequency. First, the design procedure and accuracy of the optimum FLC are illustrated and investigated through simulations conducted in a MATLAB environment. The LSA-based FLC (LSA-FL) are compared with differential search algorithm (DSA)-based FLC (DSA-FL) and particle swarm optimization (PSO)-based FLC (PSO-FL). Finally, the robustness of the LSA-FL is further investigated with a hardware that is operated via an eZdsp F28335 control board. Simulation and experimental results show that the proposed controller can successfully obtain the desired output when different loads are connected to the system. The inverter also has a reasonably low steady-state error and fast response to reference variation.http://www.mdpi.com/1996-1073/9/3/120lightning search algorithm (LSA)fuzzy logic controller (FLC)inverterphotovoltaic (PV)space vector pulse width modulation (SVPWM)eZdsp F28335
collection DOAJ
language English
format Article
sources DOAJ
author Ammar Hussein Mutlag
Azah Mohamed
Hussain Shareef
spellingShingle Ammar Hussein Mutlag
Azah Mohamed
Hussain Shareef
A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board
Energies
lightning search algorithm (LSA)
fuzzy logic controller (FLC)
inverter
photovoltaic (PV)
space vector pulse width modulation (SVPWM)
eZdsp F28335
author_facet Ammar Hussein Mutlag
Azah Mohamed
Hussain Shareef
author_sort Ammar Hussein Mutlag
title A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board
title_short A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board
title_full A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board
title_fullStr A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board
title_full_unstemmed A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board
title_sort nature-inspired optimization-based optimum fuzzy logic photovoltaic inverter controller utilizing an ezdsp f28335 board
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2016-02-01
description Photovoltaic (PV) inverters essentially convert DC quantities, such as voltage and current, to AC quantities whose magnitude and frequency are controlled to obtain the desired output. Thus, the performance of an inverter depends on its controller. Therefore, an optimum fuzzy logic controller (FLC) design technique for PV inverters using a lightning search algorithm (LSA) is presented in this study. In a conventional FLC, the procedure for obtaining membership functions (MFs) is usually implemented using trial and error, which does not lead to satisfactory solutions in many cases. Therefore, this study presents a technique for obtaining MFs that avoids the exhaustive traditional trial-and-error procedure. This technique is implemented during the inverter design phase by generating adaptive MFs based on the evaluation results of the objective function formulated with LSA. The mean squared error (MSE) of the inverter output voltage is used as an objective function in this study. LSA optimizes the MFs such that the inverter provides the lowest MSE for the output voltage, and the performance of the PV inverter output is improved in terms of amplitude and frequency. First, the design procedure and accuracy of the optimum FLC are illustrated and investigated through simulations conducted in a MATLAB environment. The LSA-based FLC (LSA-FL) are compared with differential search algorithm (DSA)-based FLC (DSA-FL) and particle swarm optimization (PSO)-based FLC (PSO-FL). Finally, the robustness of the LSA-FL is further investigated with a hardware that is operated via an eZdsp F28335 control board. Simulation and experimental results show that the proposed controller can successfully obtain the desired output when different loads are connected to the system. The inverter also has a reasonably low steady-state error and fast response to reference variation.
topic lightning search algorithm (LSA)
fuzzy logic controller (FLC)
inverter
photovoltaic (PV)
space vector pulse width modulation (SVPWM)
eZdsp F28335
url http://www.mdpi.com/1996-1073/9/3/120
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