PV boost converter conditioning using neural network
This master report presents a voltage control system for DC-DC boost converter integrated with Photovoltaic (PV) array using optimized feed-forward neural network controller. A specific output voltage of a boost converter is regulated at a constant value under input voltage variations caused by a...
| Main Author: | |
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6627/ http://eprints.uthm.edu.my/6627/1/24p%20AIZAT%20ABD%20AZIZ.pdf http://eprints.uthm.edu.my/6627/2/AIZAT%20ABD%20AZIZ%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6627/3/AIZAT%20ABD%20AZIZ%20WATERMARK.pdf |
| _version_ | 1848888865065009152 |
|---|---|
| author | Abd Aziz, Aizat |
| author_facet | Abd Aziz, Aizat |
| author_sort | Abd Aziz, Aizat |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | This master report presents a voltage control system for DC-DC boost converter
integrated with Photovoltaic (PV) array using optimized feed-forward neural network
controller. A specific output voltage of a boost converter is regulated at a constant
value under input voltage variations caused by a sudden changes in irradiation for a
purpose of supplying a stabilize dc voltage to Base Transceiver Station (BTS)
telecommunication equipment that required a 48V dc input supply to be operated.
For a given solar irradiance, the tracking algorithm changes the duty ratio of the
converter such that the output voltage produced equals to 48V. This is done by the
feed-forward loop, which generates an error signal by comparing converter output
voltage and reference voltage. Depending on the error and change of error signals,
the neural network controller generates a control signal for the pulse widthmodulation
generator which in turn adjusts
the duty ratio of the converter. The
effectiveness
of the proposed method
is verified
by developing a simulation
model
in
MATLAB-Simulink
program.
Tracking performance
of the proposed controller is
also
compared
with the conventional
proportional-integral-differential
(PID)
controller.
The simulation
results
show that the proposed neural
network controller
(NNC)
produce an improvement
of control
performance
compared
to the PID
controller. |
| first_indexed | 2025-11-15T20:17:04Z |
| format | Thesis |
| id | uthm-6627 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-15T20:17:04Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-66272022-03-10T03:36:55Z http://eprints.uthm.edu.my/6627/ PV boost converter conditioning using neural network Abd Aziz, Aizat TK7800-8360 Electronics This master report presents a voltage control system for DC-DC boost converter integrated with Photovoltaic (PV) array using optimized feed-forward neural network controller. A specific output voltage of a boost converter is regulated at a constant value under input voltage variations caused by a sudden changes in irradiation for a purpose of supplying a stabilize dc voltage to Base Transceiver Station (BTS) telecommunication equipment that required a 48V dc input supply to be operated. For a given solar irradiance, the tracking algorithm changes the duty ratio of the converter such that the output voltage produced equals to 48V. This is done by the feed-forward loop, which generates an error signal by comparing converter output voltage and reference voltage. Depending on the error and change of error signals, the neural network controller generates a control signal for the pulse widthmodulation generator which in turn adjusts the duty ratio of the converter. The effectiveness of the proposed method is verified by developing a simulation model in MATLAB-Simulink program. Tracking performance of the proposed controller is also compared with the conventional proportional-integral-differential (PID) controller. The simulation results show that the proposed neural network controller (NNC) produce an improvement of control performance compared to the PID controller. 2013-07 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/6627/1/24p%20AIZAT%20ABD%20AZIZ.pdf text en http://eprints.uthm.edu.my/6627/2/AIZAT%20ABD%20AZIZ%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/6627/3/AIZAT%20ABD%20AZIZ%20WATERMARK.pdf Abd Aziz, Aizat (2013) PV boost converter conditioning using neural network. Masters thesis, Universiti Tun Hussein Malaysia. |
| spellingShingle | TK7800-8360 Electronics Abd Aziz, Aizat PV boost converter conditioning using neural network |
| title | PV boost converter conditioning using neural network |
| title_full | PV boost converter conditioning using neural network |
| title_fullStr | PV boost converter conditioning using neural network |
| title_full_unstemmed | PV boost converter conditioning using neural network |
| title_short | PV boost converter conditioning using neural network |
| title_sort | pv boost converter conditioning using neural network |
| topic | TK7800-8360 Electronics |
| url | http://eprints.uthm.edu.my/6627/ http://eprints.uthm.edu.my/6627/1/24p%20AIZAT%20ABD%20AZIZ.pdf http://eprints.uthm.edu.my/6627/2/AIZAT%20ABD%20AZIZ%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6627/3/AIZAT%20ABD%20AZIZ%20WATERMARK.pdf |