High precision experimentally validated adaptive neuro fuzzy inference system controller for DC motor drive system Article Swipe
Muhammad Akram Bhayo
,
J.A. Laghari
,
Mohammad Aljaidi
,
Mohsin Ali Koondhar
,
Ragab A. El‐Sehiemy
,
Ali Fayez Alkoradees
,
Zuhair Alaas
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-97549-4
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-97549-4
The control of a dc motor drive system is performed using two Proportional-Integral (PI) controllers, mostly comprising the outer (speed) and inner (torque) loops. However, the tuning of the PI controllers is challenging, because of the significant overshoot and substantial settling time. The overshoot cannot be absolutely removed without sacrificing the speediness. In this paper, an experimental implementation of Adaptive Neuro-Fuzzy Inference System (ANFIS) based high-precision controllers for a dc motor drive system is presented for eliminating the overshoot contemporaneously improving the settling time. In this regard, for fair comparison, Bode Plot method is used for obtaining most satisfactory values of Kp and Ki of both the controllers and the performance of the proposed ANFIS controllers is compared with the tuned PI controllers. For the sake of validation, an experimental setup, a 2-quadrant dc motor drive based on DS1104 R&D controller board from dSPACE is used. The designed ANFIS controllers are implemented and also authenticated using simulations. The obtained simulation as well as experimental results indicated that the ANFIS controller successfully eliminates the overshoot and significantly improves settling time. Thereby, outclass the tuned PI controllers by giving experimental results as 0% overshoot and just 0.18 s settling time.
Related Topics
Concepts
Computer science
DC motor
Adaptive neuro fuzzy inference system
Inference system
Neuro-fuzzy
Controller (irrigation)
Inference
Artificial intelligence
Control theory (sociology)
Control engineering
Fuzzy logic
Fuzzy control system
Engineering
Biology
Control (management)
Electrical engineering
Agronomy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41598-025-97549-4
- https://www.nature.com/articles/s41598-025-97549-4.pdf
- OA Status
- gold
- References
- 36
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409823785
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4409823785Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41598-025-97549-4Digital Object Identifier
- Title
-
High precision experimentally validated adaptive neuro fuzzy inference system controller for DC motor drive systemWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-04-25Full publication date if available
- Authors
-
Muhammad Akram Bhayo, J.A. Laghari, Mohammad Aljaidi, Mohsin Ali Koondhar, Ragab A. El‐Sehiemy, Ali Fayez Alkoradees, Zuhair AlaasList of authors in order
- Landing page
-
https://doi.org/10.1038/s41598-025-97549-4Publisher landing page
- PDF URL
-
https://www.nature.com/articles/s41598-025-97549-4.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.nature.com/articles/s41598-025-97549-4.pdfDirect OA link when available
- Concepts
-
Computer science, DC motor, Adaptive neuro fuzzy inference system, Inference system, Neuro-fuzzy, Controller (irrigation), Inference, Artificial intelligence, Control theory (sociology), Control engineering, Fuzzy logic, Fuzzy control system, Engineering, Biology, Control (management), Electrical engineering, AgronomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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36Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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