A Novel Adaptive PID Controller Design for a PEM Fuel Cell Using Stochastic Gradient Descent with Momentum Enhanced by Whale Optimizer
dc.contributor.author | Silaa, Mohammed Yousri | |
dc.contributor.author | Barambones Caramazana, Oscar | |
dc.contributor.author | Bencherif, Aissa | |
dc.date.accessioned | 2022-08-31T07:54:12Z | |
dc.date.available | 2022-08-31T07:54:12Z | |
dc.date.issued | 2022-08-20 | |
dc.identifier.citation | Electronics 11(16) : (2022) // Article ID 2610 | es_ES |
dc.identifier.issn | 2079-9292 | |
dc.identifier.uri | http://hdl.handle.net/10810/57363 | |
dc.description.abstract | This paper presents an adaptive PID using stochastic gradient descent with momentum (SGDM) for a proton exchange membrane fuel cell (PEMFC) power system. PEMFC is a nonlinear system that encounters external disturbances such as inlet gas pressures and temperature variations, for which an adaptive control law should be designed. The SGDM algorithm is employed to minimize the cost function and adapt the PID parameters according to the perturbation changes. The whale optimization algorithm (WOA) was chosen to enhance the adaptive rates in the offline mode. The proposed controller is compared with PID stochastic gradient descent (PIDSGD) and PID Ziegler Nichols tuning (PID-ZN). The control strategies’ robustnesses are tested under a variety of temperatures and loads. Unlike the PIDSGD and PID-ZN controllers, the PIDSGDM controller can attain the required control performance, such as fast convergence and high robustness. Simulation results using Matlab/Simulink have been studied and illustrate the effectiveness of the proposed controller. | es_ES |
dc.description.sponsorship | The authors wish to express their gratitude to the Basque Government through the project EKOHEGAZ (ELKARTEK KK-2021/00092), to the Diputación Foral de Álava (DFA) through the project CONAVANTER, and to the UPV/EHU through the project GIU20/063 for supporting this work. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | stochastic gradient descent with momentum | es_ES |
dc.subject | stochastic gradient descent | es_ES |
dc.subject | PID controller | es_ES |
dc.subject | whale optimization algorithm | es_ES |
dc.subject | proton exchange membrane fuel cell | es_ES |
dc.title | A Novel Adaptive PID Controller Design for a PEM Fuel Cell Using Stochastic Gradient Descent with Momentum Enhanced by Whale Optimizer | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2022-08-25T11:19:22Z | |
dc.rights.holder | © 2022 by the authors.Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/2079-9292/11/16/2610 | es_ES |
dc.identifier.doi | 10.3390/electronics11162610 | |
dc.departamentoes | Ingeniería de sistemas y automática | |
dc.departamentoeu | Sistemen ingeniaritza eta automatika |
Files in this item
This item appears in the following Collection(s)
Except where otherwise noted, this item's license is described as © 2022 by the authors.Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).