Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizer
In this paper, a novel hybrid Neural Network Algorithm-Differential Evolution (NNA-DE) optimizer which integrates both NNA and DE is proposed. The proposed hybrid NNA-DE optimizer demonstrates better performance compared to the standard NNA and the other state-of-the-art optimization algorithms. The...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016822000023 |
| _version_ | 1811275319411212288 |
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| author | Mahmoud S. AbouOmar Yixin Su Huajun Zhang Binghua Shi Lily Wan |
| author_facet | Mahmoud S. AbouOmar Yixin Su Huajun Zhang Binghua Shi Lily Wan |
| author_sort | Mahmoud S. AbouOmar |
| collection | DOAJ |
| description | In this paper, a novel hybrid Neural Network Algorithm-Differential Evolution (NNA-DE) optimizer which integrates both NNA and DE is proposed. The proposed hybrid NNA-DE optimizer demonstrates better performance compared to the standard NNA and the other state-of-the-art optimization algorithms. The proposed hybrid NNA-DE algorithm is then employed for optimizing an observer-based interval type-2 fuzzy PID (OB-IT2FPID) controller applied to the proton exchange membrane fuel cell (PEMFC) air feeding system. The whole design parameters of the OB-IT2FPID controller including the scaling factors, interval type-2 membership function parameters and the footprint-of-uncertainty (FOU) are optimized using the proposed hybrid NNA-DE algorithm. The results show that the proposed NNA-DE optimized OB-IT2FPID controller achieves better performance in terms of set-point tracking, disturbance rejection and the time-domain performance indices. The robustness of the proposed NNA-DE optimized OB-IT2FPID controller against parametric uncertainty in the PEMFC air-feeding system is tested. The proposed controller demonstrated better robustness against parameter uncertainty in the system. Processor-in-the-Loop (PIL) approach is adopted to validate the performance of the proposed controller on embedded control hardware. |
| first_indexed | 2024-04-12T23:36:37Z |
| format | Article |
| id | doaj.art-31a12f59cc254eb1bf02969fbed33aa6 |
| institution | Directory Open Access Journal |
| issn | 1110-0168 |
| language | English |
| last_indexed | 2024-04-12T23:36:37Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj.art-31a12f59cc254eb1bf02969fbed33aa62022-12-22T03:12:07ZengElsevierAlexandria Engineering Journal1110-01682022-09-0161973537375Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizerMahmoud S. AbouOmar0Yixin Su1Huajun Zhang2Binghua Shi3Lily Wan4School of Automation, Wuhan University of Technology, Wuhan 430070, China; Industrial Electronics and Control Engineering Department, Faculty of Electronic Engineering, Menoufia University, 32952, EgyptSchool of Automation, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Automation, Wuhan University of Technology, Wuhan 430070, China; Corresponding author at: School of Automation, Wuhan University of Technology, Wuhan 430070, China.School of Automation, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Automation, Wuhan University of Technology, Wuhan 430070, ChinaIn this paper, a novel hybrid Neural Network Algorithm-Differential Evolution (NNA-DE) optimizer which integrates both NNA and DE is proposed. The proposed hybrid NNA-DE optimizer demonstrates better performance compared to the standard NNA and the other state-of-the-art optimization algorithms. The proposed hybrid NNA-DE algorithm is then employed for optimizing an observer-based interval type-2 fuzzy PID (OB-IT2FPID) controller applied to the proton exchange membrane fuel cell (PEMFC) air feeding system. The whole design parameters of the OB-IT2FPID controller including the scaling factors, interval type-2 membership function parameters and the footprint-of-uncertainty (FOU) are optimized using the proposed hybrid NNA-DE algorithm. The results show that the proposed NNA-DE optimized OB-IT2FPID controller achieves better performance in terms of set-point tracking, disturbance rejection and the time-domain performance indices. The robustness of the proposed NNA-DE optimized OB-IT2FPID controller against parametric uncertainty in the PEMFC air-feeding system is tested. The proposed controller demonstrated better robustness against parameter uncertainty in the system. Processor-in-the-Loop (PIL) approach is adopted to validate the performance of the proposed controller on embedded control hardware.http://www.sciencedirect.com/science/article/pii/S1110016822000023Neural Network Algorithm-Differential Evolution (NNA-DE)Observer-Based Interval Type-2 Fuzzy PID (OB-IT2FPID) ControllerOxygen Excess Ratio (OER)PEM Fuel Cells (PEMFC)Processor-in-the-Loop (PIL) |
| spellingShingle | Mahmoud S. AbouOmar Yixin Su Huajun Zhang Binghua Shi Lily Wan Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizer Alexandria Engineering Journal Neural Network Algorithm-Differential Evolution (NNA-DE) Observer-Based Interval Type-2 Fuzzy PID (OB-IT2FPID) Controller Oxygen Excess Ratio (OER) PEM Fuel Cells (PEMFC) Processor-in-the-Loop (PIL) |
| title | Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizer |
| title_full | Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizer |
| title_fullStr | Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizer |
| title_full_unstemmed | Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizer |
| title_short | Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizer |
| title_sort | observer based interval type 2 fuzzy pid controller for pemfc air feeding system using novel hybrid neural network algorithm differential evolution optimizer |
| topic | Neural Network Algorithm-Differential Evolution (NNA-DE) Observer-Based Interval Type-2 Fuzzy PID (OB-IT2FPID) Controller Oxygen Excess Ratio (OER) PEM Fuel Cells (PEMFC) Processor-in-the-Loop (PIL) |
| url | http://www.sciencedirect.com/science/article/pii/S1110016822000023 |
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