A Novel Adaptive PID Controller Design for a PEM Fuel Cell Using Stochastic Gradient Descent with Momentum Enhanced by Whale Optimizer

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.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

A New MPPT-Based Extended Grey Wolf Optimizer for Stand-Alone PV System: A Performance Evaluation versus Four Smart MPPT Techniques in Diverse Scenarios

Photovoltaic (PV) systems play a crucial role in clean energy systems. Effective maximum power point tracking (MPPT) techniques are essential to optimize their performance. However, conventional MPPT methods exhibit limitations and challenges in real-world scenarios characterized by rapidly changing environmental factors and various operating conditions. To address these challenges, this paper presents a performance evaluation of a novel extended grey wolf optimizer (EGWO). The EGWO has been meticulously designed in order to improve the efficiency of PV systems by rapidly tracking and maintaining the maximum power point (MPP). In this study, a comparison is made between the EGWO and other prominent MPPT techniques, including the grey wolf optimizer (GWO), equilibrium optimization algorithm (EOA), particle swarm optimization (PSO) and sin cos algorithm (SCA) techniques. To evaluate these MPPT methods, a model of a PV module integrated with a DC/DC boost converter is employed, and simulations are conducted using Simulink-MATLAB software under standard test conditions (STC) and various environmental conditions. In particular, the results demonstrate that the novel EGWO outperforms the GWO, EOA, PSO and SCA techniques and shows fast tracking speed, superior dynamic response, high robustness and minimal power fluctuations across both STC and variable conditions. Thus, a power fluctuation of 0.09 W could be achieved by using the proposed EGWO technique. Finally, according to these results, the proposed approach can offer an improvement in energy consumption. These findings underscore the potential benefits of employing the novel MPPT EGWO to enhance the efficiency and performance of MPPT in PV systems. Further exploration of this intelligent technique could lead to significant advancements in optimizing PV system performance, making it a promising option for real-world applications.The authors wish to express their gratitude to the Basque Government, through the project EKOHEGAZ II (ELKARTEK KK-2023/00051); 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

Real-Time Implementation of a New MPPT Control Method for a DC-DC Boost Converter Used in a PEM Fuel Cell Power System

settings Open AccessArticle Real-Time Implementation of a New MPPT Control Method for a DC-DC Boost Converter Used in a PEM Fuel Cell Power System by Mohamed Derbeli 1,2,* [OrcID] , Oscar Barambones 1 [OrcID] , Mohammed Yousri Silaa 1 [OrcID] and Cristian Napole 1 [OrcID] 1 Engineering School of Vitoria, University of the Basque Country UPV/EHU, Nieves Cano 12, 1006 Vitoria, Spain 2 National Engineering School of Gabes, University of Gabes, Omar Ibn-Elkhattab, 6029 Gabes, Tunisia * Author to whom correspondence should be addressed. Actuators 2020, 9(4), 105; https://doi.org/10.3390/act9040105 Received: 30 August 2020 / Revised: 25 September 2020 / Accepted: 10 October 2020 / Published: 16 October 2020 (This article belongs to the Section High Torque/Power Density Actuators) Download PDF Browse Figures Abstract Polymer electrolyte membrane (PEM) fuel cells demonstrate potential as a comprehensive and general alternative to fossil fuel. They are also considered to be the energy source of the twenty-first century. However, fuel cell systems have non-linear output characteristics because of their input variations, which causes a significant loss in the overall system output. Thus, aiming to optimize their outputs, fuel cells are usually coupled with a controlled electronic actuator (DC-DC boost converter) that offers highly regulated output voltage. High-order sliding mode (HOSM) control has been effectively used for power electronic converters due to its high tracking accuracy, design simplicity, and robustness. Therefore, this paper proposes a novel maximum power point tracking (MPPT) method based on a combination of reference current estimator (RCE) and high-order prescribed convergence law (HO-PCL) for a PEM fuel cell power system. The proposed MPPT method is implemented practically on a hardware 360W FC-42/HLC evaluation kit. The obtained experimental results demonstrate the success of the proposed method in extracting the maximum power from the fuel cell with high tracking performance.This work was partially supported by Eusko Jaurlaritza/Gobierno Vasco [grant number SMAR3NAK ELKARTEK KK-2019/00051]; the Provincial Council of Alava (DFA) [grant number CONAVAUTIN 2] (Collaboration Agreement)

Design and Implementation of High Order Sliding Mode Control for PEMFC Power System

Fuel cells are considered as one of the most promising methods to produce electrical energy due to its high-efficiency level that reaches up to 50%, as well as high reliability with no polluting effects. However, scientists and researchers are interested more in proton exchange membrane fuel cells (PEMFCs). Thus, it has been considered as an ideal solution to many engineering applications. The main aim of this work is to keep the PEMFC operating at an adequate power point. To this end, conventional first-order sliding mode control (SMC) is used. However, the chattering phenomenon, which is caused by the SMC leads to a low control accuracy and heat loss in the energy circuits. In order to overcome these drawbacks, quasi-continuous high order sliding mode control (QC-HOSM) is proposed so as to improve the power quality and performance. The control stability is proven via the Lyapunov theory. The closed-loop system consists of a PEM fuel cell, a step-up converter, a DSPACE DS1104, SMC and QC-HOSM algorithms and a variable load resistance. In order to demonstrate the effectiveness of the proposed control scheme, experimental results are compared with the conventional SMC. The obtained results show that a chattering reduction of 84% could be achieved using the proposed method.This work was partially supported by Eusko Jaurlaritza/Gobierno Vasco [grant number SMAR3NAK ELKARTEK KK-2019/00051]; the Provincial Council of Alava (DFA) [grant number CONAVAUTIN 2] (Collaboration Agreement)

Fractional Order PID Design for a Proton Exchange Membrane Fuel Cell System Using an Extended Grey Wolf Optimizer

This paper presents a comparison of optimizers for tuning a fractional-order proportional-integral-derivative (FOPID) and proportional-integral-derivative (PID) controllers, which were applied to a DC/DC boost converter. Grey wolf optimizer (GWO) and extended grey wolf optimizer (EGWO) have been chosen to achieve suitable parameters. This strategy aims to improve and optimize a proton exchange membrane fuel cell (PEMFC) output power quality through its link with the boost converter. The model and controllers have been implemented in a MATLAB/SIMULINK environment. This study has been conducted to compare the effectiveness of the proposed controllers in the transient, accuracy in tracking the reference current, steady-state, dynamic responses, overshoots, and response time. Results showed that the combination EGWO-FOPID had significant advantages over the rest of the optimized controllersThe 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

Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation

first_page settings Open AccessArticle Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation by Cristian Napole 1,* [OrcID] , Oscar Barambones 1,* [OrcID] , Isidro Calvo 1 [OrcID] , Mohamed Derbeli 1 [OrcID] , Mohammed Yousri Silaa 1 [OrcID] and Javier Velasco 2 [OrcID] 1 System Engineering and Automation Deparment, Faculty of Engineering of Vitoria-Gasteiz, Basque Country University (UPV/EHU), 01006 Vitoria-Gasteiz, Spain 2 Fundación Centro de Tecnologías Aeronáuticas (CTA), Juan de la Cierva 1, 01510 Miñano, Spain * Authors to whom correspondence should be addressed. Mathematics 2020, 8(11), 2071; https://doi.org/10.3390/math8112071 Received: 23 October 2020 / Revised: 16 November 2020 / Accepted: 17 November 2020 / Published: 20 November 2020 (This article belongs to the Special Issue Fuzzy Applications in Industrial Engineering) Download PDF Browse Figures Abstract Piezoelectric actuators (PEA) are devices that are used for nano- microdisplacement due to their high precision, but one of the major issues is the non-linearity phenomena caused by the hysteresis effect, which diminishes the positioning performance. This study presents a novel control structure in order to reduce the hysteresis effect and increase the PEA performance by using a fuzzy logic control (FLC) combined with a Hammerstein–Wiener (HW) black-box mapping as a feedforward (FF) compensation. In this research, a proportional-integral-derivative (PID) was contrasted with an FLC. From this comparison, the most accurate was taken and tested with a complex structure with HW-FF to verify the accuracy with the increment of complexity. All of the structures were implemented in a dSpace platform to control a commercial Thorlabs PEA. The tests have shown that an FLC combined with HW was the most accurate, since the FF compensate the hysteresis and the FLC reduced the errors; the integral of the absolute error (IAE), the root-mean-square error (RMSE), and relative root-mean-square-error (RRMSE) for this case were reduced by several magnitude orders when compared to the feedback structures. As a conclusion, a complex structure with a novel combination of FLC and HW-FF provided an increment in the accuracy for a high-precision PEA.This research was funded by Basque Government and UPV/EHU projects

High-Performance Tracking for Piezoelectric Actuators Using Super-Twisting Algorithm Based on Artificial Neural Networks

Piezoelectric actuators (PEA) are frequently employed in applications where nano-Micr-odisplacement is required because of their high-precision performance. However, the positioning is affected substantially by the hysteresis which resembles in an nonlinear effect. In addition, hysteresis mathematical models own deficiencies that can influence on the reference following performance. The objective of this study was to enhance the tracking accuracy of a commercial PEA stack actuator with the implementation of a novel approach which consists in the use of a Super-Twisting Algorithm (STA) combined with artificial neural networks (ANN). A Lyapunov stability proof is bestowed to explain the theoretical solution. Experimental results of the proposed method were compared with a proportional-integral-derivative (PID) controller. The outcomes in a real PEA reported that the novel structure is stable as it was proved theoretically, and the experiments provided a significant error reduction in contrast with the PID.This research was funded by Basque Government and UPV/EHU projects

An Efficient and Robust Current Control for Polymer Electrolyte Membrane Fuel Cell Power System

Taking into account the restricted ability of polymer electrolyte membrane fuel cell (PEMFC) to generate energy, it is compulsory to present techniques, in which an efficient operating power can be achieved. In many applications, the PEMFC is usually coupled with a high step-up DC-DC power converter which not only provides efficient power conversion, but also offers highly regulated output voltage. Due to the no-linearity of the PEMFC power systems, the application of conventional linear controllers such as proportional-integral (PI) did not succeed to drive the system to operate precisely in an adequate power point. Therefore, this paper proposes a robust non-linear integral fast terminal sliding mode control (IFTSMC) aiming to improve the power quality generated by the PEMFC; besides, a digital filter is designed and implemented to smooth the signals from the chattering effect of the IFTSMC. The stability proof of the IFTSMC is demonstrated via Lyapunov analysis. The proposed control scheme is designed for an experimental closed-loop system which consisted of a Heliocentric hy-Expert™ FC-50W, MicroLabBox dSPACE DS1202, step-up DC-DC power converter and programmable DC power supplies. Comparative results with the PI controller indicate that a reduction of 96% in the response time could be achieved using the suggested algorithm; where, up to more than 91% of the chattering phenomenon could be eliminated via the application of the digital filter.The authors wish to express their gratitude to the Basque Government through the project SMAR3NAK (ELKARTEK KK-2019/00051), to the Diputación Foral de Álava (DFA) through the project CONAVAUTIN 2 and to the UPV/EHU for supporting this work

PEMFC Current Control Using a Novel Compound Controller Enhanced by the Black Widow Algorithm: A Comprehensive Simulation Study

Proton exchange membrane fuel cells (PEMFCs) play a crucial role in clean energy systems. Effective control of these systems is essential to optimize their performance. However, conventional control methods exhibit limitations in handling disturbances and ensuring robust control. To address these challenges, this paper presents a novel PI sliding mode controller-based super-twisting algorithm (PISMCSTA). The proposed controller is applied to drive the DC/DC boost converter in order to improve the PEMFC output power quality. In addition, the black widow optimization algorithm (BWOA) has been chosen to enhance and tune the PISMCSTA parameters according to the disturbance changes. The performance of the PISMCSTA is compared with the conventional STA controller. Comparative results are obtained from numerical simulations and these results show that the developed proposed PISMCSTA gives better results when compared to the conventional STA. A reduction of up to 8.7% in the response time could be achieved and up to 66% of the chattering effect could be eliminated by using the proposed controller. Finally, according to these results, the proposed approach can offer an improvement in energy consumption

Tracking Control for Piezoelectric Actuators with Advanced Feed-Forward Compensation Combined with PI Control

Piezoelectric Actuators (PEAs) are devices that can support large actuation forces compared to their small size and are widely used in high-precision applications where micro- and nano-positioning are required. Nonetheless, these actuators have undeniable non-linearities, the well-known ones being creep, vibration dynamics, and hysteresis. The latter originate from a combination of mechanical strain and electric field action; as a consequence, these can affect the PEA tracking performance and even reach instability. The scope of this paper is to reduce the hysteresis effect using and comparing different control strategies like feedback with a Feed-Forward (FF) structure, which is often used to compensate the non-linearities and diminish the errors due to uncertainties. In this research, black-box models are analyzed; subsequently, a classic feedback control like Proportional-Integral (PI) control is combined with the FF methods proposed separately and embedded into a dSpace platform to perform real-time experiments. Results are analyzed in-depth in terms of the error, the control signal, and the Integral of the Absolute Error (IAE). It is found that with the proposed methods, the hysteresis effect could be diminished to acceptable ranges for high-precision tracking with a satisfactory control signal