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

Silaa, Mohammed Yousri; Barambones, Óscar; Derbeli, Mohamed; Napole, Cristian; Bencherif, Aissa

doi:10.3390/pr10030450

Cited by 18 publications

(12 citation statements)

References 51 publications

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“…Since then, a lot of work has been put into developing fractional-order PID controllers. Early studies were done by Podlubny [30] and Oustaloup et al [31][32][33][34][35]. In the research article [36][37][38][39][40] tuning recommendations are used to design the FPI controllers.…”

Section: Stage 1: An Integral Proportional Controller Designmentioning

confidence: 99%

Optimization of PEMFC pressure control using fractional PI/D controller with non-integer order: design and experimental evaluation

Routh,

Ghosh,

Dey

et al. 2024

Eng. Res. Express

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The fuel-based proton exchange membrane (PEM) fuel cell is a promising technology for clean energy production owing to the several advantages including high efficiency (around 80% theoretical), quiet in operation, and almost zero emission as compared to conventional internal combustion engine. Only hydrogen and oxygen are supplied at the anode and cathode, respectively to generate power and water is produced as by product. However, it suffers to achieve its maximum theoretical efficiency due to lack of flow/pressure management of hydrogen and oxygen in the PEMFC stack which also causes flooding within the cell and reduce the performance of the catalyst and reduces the efficiency. The higher efficiency can be achieved with the proper control of the hydrogen and oxygen inlet flow rate and pressure at the PEMFC. Since it's crucial to maintaining a consistent supply of exponential pressure, the main focus of this work is pressure regulation at the PEMFC cathode side. A fractional PI/D controller is designed to operate the PEMFC system more realistically. There are three primary objectives of this research work. In the first step, monitoring the PEMFC operating pressure to find out the suitable fractional PI-D controller for a given resilience level, which has the lowest Integration Absolute Error (IAE) to disturbances. The robustness level and/or threshold peak is considered as a tuning parameter for the evaluation. Second, compare the best IAE performance of the fractional PI-D controller with that of simple SIMC rules, where a certain level of resilience is achieved by varying the SIMC tuning variable. Through this comparison, the effectiveness of the recommended controller in achieving the optimal plant performance is evaluated. Thirdly, design a non-integer order PEMFC plant with a fractional controller using MATLAB software and compare the results with existing models. This comparison provides insight into the practical performance of the proposed controller. The results shows that the developed fractional PI/D controller is able to control the pressure very efficiently at the PEMFC cathode side. The findings further emphasise on the important to consider the resilience and robustness levels at the time of developing control systems for PEMFCs. The efficacy of the suggested unique technique is further confirmed by contrasting the suggested controller with the developed models.

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Section: Stage 1: An Integral Proportional Controller Designmentioning

confidence: 99%

Optimization of PEMFC pressure control using fractional PI/D controller with non-integer order: design and experimental evaluation

Routh,

Ghosh,

Dey

et al. 2024

Eng. Res. Express

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show abstract

“…Moreover, the FOPID controllers could lead to lower energy consumption as a result of their fine-tuning control action, as in [27]. Additionally, the FOPID controllers were employed in different renewable energy resources, like wind energy [28], solar energy [29], fuel cells [30], and hydroelectric [31]. In addition, the FOPID control strategy was utilized in the speed control of a PMSM [32].…”

Section: Objectives and Contributionsmentioning

confidence: 99%

Optimal Design of Fractional-Order PID Controllers for a Nonlinear AWS Wave Energy Converter Using Hybrid Jellyfish Search and Particle Swarm Optimization

Ali,

Ahmed,

Hasanien

et al. 2023

Fractal Fract

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In this study, a nonlinear Archimedes wave swing (AWS) energy conversion system was employed to enable the use of irregular sea waves to provide useful electricity. Instead of the conventional PI controllers used in prior research, this study employed fractional-order PID (FOPID) controllers to control the back-to-back configuration of AWS. The aim was to maximize the energy yield from waves and maintain the grid voltage and the capacitor DC link voltage at predetermined values. In this study, six FOPID controllers were used to accomplish the control goals, leading to an array of thirty parameters required to be fine-tuned. In this regard, a hybrid jellyfish search optimizer and particle swarm optimization (HJSPSO) algorithm was adopted to select the optimal control gains. Verification of the performance of the proposed FOPID control system was achieved by comparing the system results to two conventional PID controllers and one FOPID controller. The conventional PID controllers were tuned using a recently presented metaheuristic algorithm called the Coot optimization algorithm (COOT) and the classical particle swarm optimization algorithm (PSO). Moreover, the FOPID was also tuned using the well-known genetic algorithm (GA). The system investigated in this study was subjected to various unsymmetrical and symmetrical fault disturbances. When compared with the standard COOT-PID, PSO-PID, and GA-FOPID controllers, the HJSPSO-FOPID results show a significant improvement in terms of performance and preserving control goals during system instability

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“…The working duty cycle of the DC/DC converter used for FC interface is set by the MPPT controllers during MPP operation. [18][19][20] In the base works, [21][22][23] several MPPT techniques such as perturb & observe (P&O), incremental conductance (INC), fuzzy logic control (FLC), adaptive neurofuzzy inference system (ANFIS), etc, for obtaining maximum power extraction from FCs are used. However, the baseline models [24][25][26] have the major drawbacks of high tracking time, reduced steady-state performance, high cost, and system complexity.…”

Section: Doi: 101002/ente202300556mentioning

confidence: 99%

An Amplified Salp Swarm Optimization Algorithm for Maximum Power Point Tracking Control of Proton Exchange Membrane Fuel Cells

Injarapu Edukondala Sanyasi,

Sambana,

Chilukoti

et al. 2023

Energy Tech

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The proton exchange membrane fuel cell (PEMFC), one of the many fuel cell varieties on the market, is distinguished by its low temperatures of operation, high reliability, and extended lifespan. The fuel cell system's maximum output can only be achieved at one specific operating point under varying operating circumstances. Hence, it is essential to get the most power possible from the PEMFC for improved functioning and optimal exploitation of grid systems. Thus, the design of a maximum power point tracking (MPPT) controller for a PEMFC power system using an amplified salp swarm optimization (AS2O) algorithm is focused on. Here, an interleaved Luo converter is also used to produce a regulated output voltage with less switching stress and frequency. Moreover, the proposed work intends to effectively satisfy the energy demand of grid systems by obtaining the maximum electrical energy from the PEMFCs with less harmonics and low system complexity. The simulation and performance results of the proposed AS2O‐MPPT controlling model are validated and compared using several parameters using MATLAB/Simulink tool. Using the proposed controlling technique, the total harmonics distortion is reduced up to 1.16%, with the settling time of 0.0062 s, rise time of 0.0010 s, and peak overshoot of 0.255 W.

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

Cited by 18 publications

References 51 publications

Optimization of PEMFC pressure control using fractional PI/D controller with non-integer order: design and experimental evaluation

Optimization of PEMFC pressure control using fractional PI/D controller with non-integer order: design and experimental evaluation

Optimal Design of Fractional-Order PID Controllers for a Nonlinear AWS Wave Energy Converter Using Hybrid Jellyfish Search and Particle Swarm Optimization

An Amplified Salp Swarm Optimization Algorithm for Maximum Power Point Tracking Control of Proton Exchange Membrane Fuel Cells

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