Multi-objective Newton-Raphson-based optimizer for fractional-order control of PEM fuel cells

This paper proposes a novel Multi-objective Newton-Raphson-based Optimizer (MONRBO) for solving multi-objective optimization problems. The proposed algorithm adopts the nondominated sorting and the crowding distance sorting techniques to effectively explore the Pareto front. The performance of the p...

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Main Authors: Mahmoud S. AbouOmar, Sami El Ferik
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Results in Engineering
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025002403
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author Mahmoud S. AbouOmar
Sami El Ferik
author_facet Mahmoud S. AbouOmar
Sami El Ferik
author_sort Mahmoud S. AbouOmar
collection DOAJ
description This paper proposes a novel Multi-objective Newton-Raphson-based Optimizer (MONRBO) for solving multi-objective optimization problems. The proposed algorithm adopts the nondominated sorting and the crowding distance sorting techniques to effectively explore the Pareto front. The performance of the proposed MONRBO algorithm is validated using a set of constrained and unconstrained benchmark problems. Results demonstrate the competitive capabilities of the proposed MONRBO algorithm compared to established algorithms including the Nondominated Sorting Genetic Algorithm-II (NSGA-II), Multi-objective Evolutionary Algorithm based on Decomposition (MOEA-D), and Multi-objective Particle Swarm Optimization with Crowding Distance (MOPSO-CD). To further validate its practical applicability, the proposed MONRBO algorithm is employed to obtain the Pareto front of conflicting objectives for an observer-based nonlinear fractional-order PIλDμ controller applied to the PEM fuel cell air-feeding system. The first objective is preventing oxygen starvation by minimizing the integral of time-weighted absolute error between the reference and the actual oxygen excess ratio. The second objective is minimizing the compressor power to increase the net power output of the PEMFC stack. Results prove the efficiency of the proposed MONRBO algorithm for solving the PEMFC air-feeding multi-objective control problem.
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publishDate 2025-03-01
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series Results in Engineering
spelling doaj-art-829a764b851148a594fed7f898431b2f2025-02-02T05:29:14ZengElsevierResults in Engineering2590-12302025-03-0125104152Multi-objective Newton-Raphson-based optimizer for fractional-order control of PEM fuel cellsMahmoud S. AbouOmar0Sami El Ferik1Interdisciplinary Research Center for Smart Mobility and Logistics, King Fahd University of Petroleum & Minerals, 31261, Saudi Arabia; Control and Instrumentation Engineering Department, King Fahd University of Petroleum & Minerals, 31261, Saudi Arabia; Corresponding author.Interdisciplinary Research Center for Smart Mobility and Logistics, King Fahd University of Petroleum & Minerals, 31261, Saudi Arabia; Control and Instrumentation Engineering Department, King Fahd University of Petroleum & Minerals, 31261, Saudi ArabiaThis paper proposes a novel Multi-objective Newton-Raphson-based Optimizer (MONRBO) for solving multi-objective optimization problems. The proposed algorithm adopts the nondominated sorting and the crowding distance sorting techniques to effectively explore the Pareto front. The performance of the proposed MONRBO algorithm is validated using a set of constrained and unconstrained benchmark problems. Results demonstrate the competitive capabilities of the proposed MONRBO algorithm compared to established algorithms including the Nondominated Sorting Genetic Algorithm-II (NSGA-II), Multi-objective Evolutionary Algorithm based on Decomposition (MOEA-D), and Multi-objective Particle Swarm Optimization with Crowding Distance (MOPSO-CD). To further validate its practical applicability, the proposed MONRBO algorithm is employed to obtain the Pareto front of conflicting objectives for an observer-based nonlinear fractional-order PIλDμ controller applied to the PEM fuel cell air-feeding system. The first objective is preventing oxygen starvation by minimizing the integral of time-weighted absolute error between the reference and the actual oxygen excess ratio. The second objective is minimizing the compressor power to increase the net power output of the PEMFC stack. Results prove the efficiency of the proposed MONRBO algorithm for solving the PEMFC air-feeding multi-objective control problem.http://www.sciencedirect.com/science/article/pii/S2590123025002403Multi-objective Newton-Raphson-based optimizer (MONRBO)Pareto front (PF)Observer-based nonlinear fractional-order PIλ Dμ controller;PEM Fuel Cells (PEMFC)
spellingShingle Mahmoud S. AbouOmar
Sami El Ferik
Multi-objective Newton-Raphson-based optimizer for fractional-order control of PEM fuel cells
Results in Engineering
Multi-objective Newton-Raphson-based optimizer (MONRBO)
Pareto front (PF)
Observer-based nonlinear fractional-order PIλ Dμ controller;PEM Fuel Cells (PEMFC)
title Multi-objective Newton-Raphson-based optimizer for fractional-order control of PEM fuel cells
title_full Multi-objective Newton-Raphson-based optimizer for fractional-order control of PEM fuel cells
title_fullStr Multi-objective Newton-Raphson-based optimizer for fractional-order control of PEM fuel cells
title_full_unstemmed Multi-objective Newton-Raphson-based optimizer for fractional-order control of PEM fuel cells
title_short Multi-objective Newton-Raphson-based optimizer for fractional-order control of PEM fuel cells
title_sort multi objective newton raphson based optimizer for fractional order control of pem fuel cells
topic Multi-objective Newton-Raphson-based optimizer (MONRBO)
Pareto front (PF)
Observer-based nonlinear fractional-order PIλ Dμ controller;PEM Fuel Cells (PEMFC)
url http://www.sciencedirect.com/science/article/pii/S2590123025002403
work_keys_str_mv AT mahmoudsabouomar multiobjectivenewtonraphsonbasedoptimizerforfractionalordercontrolofpemfuelcells
AT samielferik multiobjectivenewtonraphsonbasedoptimizerforfractionalordercontrolofpemfuelcells