Autor: |
Mahmoud S. AbouOmar, Yixin Su, Huajun Zhang, Binghua Shi, Lily Wan |
Jazyk: |
angličtina |
Rok vydání: |
2022 |
Předmět: |
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Zdroj: |
Alexandria Engineering Journal, Vol 61, Iss 9, Pp 7353-7375 (2022) |
Druh dokumentu: |
article |
ISSN: |
1110-0168 |
DOI: |
10.1016/j.aej.2021.12.072 |
Popis: |
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. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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