Multi-group grey wolf optimizer (MG-GWO) for estimating photovoltaic solar cell model

Al-Shabi, Mohammad; Ghenaï, Chaouki; Bettayeb, Maâmar; Ahmad, Fahad Faraz; Assad, Mamdouh El Haj

doi:10.1007/s10973-020-09895-2

Cited by 37 publications

(24 citation statements)

References 49 publications

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“…Moreover, the usage of the machine learning could you help losing weight and improve the life quality [13][14][15][16][17][18][19][20][21][22][23]. Moreover, metaheuristic algorithms, integrated with machine learning techniques [24][25][26][27][28][29][30][31][32][33][34][35][36], can optimize the selection of input parameters for WBV studies on weight loss and quality of life improvements, overcoming challenges related to standardized protocols and diverse parameter settings, and providing more consistent and reliable outcomes [37][38][39][40][41][42][43][44][45][46][47][48][49]. In this work, the work of [1,12] is extended to cover the effect of the human gender on the apparent mass.…”

Section: Introductionmentioning

confidence: 99%

Studying the gender effect on apparent mass during whole-body vibration using ANN

Al-Shabi

Nawayseh

2023

Smart Biomedical and Physiological Sensor Technology XX

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Artificial Neural Network (ANN) is a powerful tool to model a system using only the inputs and outputs of that system. In this paper, ANN is used to model the relation between the subject's gender to its performance while been excited in a whole-body vibration machine (WBV). For training the ANN, 20 male and 20 female subjects were observed during an experimental setup using a WBV at different vibration frequencies in the range of 20 to 45 Hz. The apparent mass was measured for the subjects at different frequencies. The input to the ANN includes body mass index, mass, and gender of the subjects along with and the excitation frequency. The ANN shows a good performance and extract the relationship with a performance that has a root mean squared error of the relative percentage error less than 9%.

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Section: Introductionmentioning

confidence: 99%

Studying the gender effect on apparent mass during whole-body vibration using ANN

Al-Shabi

Nawayseh

2023

Smart Biomedical and Physiological Sensor Technology XX

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“…The Sliding Innovation Filter (SIF) [1][2][3][4][5] is a model-based filter [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] that can be used in signal processing, fault detection, and diagnosis applications [24][25][26][27][28][29]. This type of filter utilizes a predefined model that replicates the system under investigation, and apply the input signal to stimulate that model.…”

Section: Introductionmentioning

confidence: 99%

FPGA to study the behavior of a maneuvering UGV using sliding innovation filter

Al-Shabi

Bonny

Gadsden

2023

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII

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Field programmable gate arrays (FPGAs) are increasingly popular due to their customizability, which enables them to be tailored to specific applications, resulting in minimal resource usage that saves energy and space. In this work, we used an FPGA with a Z-board from Xilinx to simulate the application of the sliding innovation filter (SIF) to a robotic arm. SIF is a predictor-corrector filter used for both linear and nonlinear systems to estimate states and/or parameters. It shares similar principles with sliding mode observer and smooth variable structure filter (SVSF) and uses a correction gain derived to satisfy Lyapunov stability, keeping the estimates near the measurements. We tested SIF on a manipulator with two joints (rotational and prismatic), using FPGA to run the simulation while tracking resource utilization. We compared the results with those of SVSF.

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“…Toledo et al proposed the two-step linear-least-square technique [22]. There is a vital benefit to the recommended approach, which is that it can gather information whether it is obtained from an I-V curve, i.e., it does not need any previous assessments and does not request information on past examinations or data about the boundaries [23,24]. It is feasible to eliminate the inherent potential (Vbi) from cells by utilizing a material-sciencebased model and an observational method considering I-V attributes [25,26].…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Novel Tabu Search Optimization Algorithm to Extract Parasitic Parameters of Solar Panel

Repalle¹,

Sarala

Mihet‐Popa

et al. 2022

Energies

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The aging of PV cells reduces their electrical performance i.e., the parasitic parameters are introduced in the solar panel. The shunt resistance (RSh), series resistance (RS), photo current (IPh), diode current (Id), and diffusion constant (a1) are known as parasitic or extraction parameters. Cracks and hotspots reduce the performance of PV cells and result in poor V–I characteristics. Certain tests are carried out over a long period of time to determine the quality of solar cells; for example, 1000 h of testing is comparable to 20 years of operation. The extraction of solar parameters is important for PV modules. The Tabu Search Optimization (TSO) algorithm is a robust meta-heuristic algorithm that was employed in this study for the extraction of parasitic parameters. Particle Swarm Optimization (PSO) and a Genetic lgorithm (GA), as well as other well-known optimization methods, were used to test the proposed method’s correctness. The other approaches included the lightning search algorithm (LSA), gravitational search algorithm (GSA), and pattern search (PS). It can be concluded that the TSO approach extracts all six parameters in a reasonably short period of time. The work presented in this paper was developed and analyzed using a MATLAB-Simulink software environment.

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Multi-group grey wolf optimizer (MG-GWO) for estimating photovoltaic solar cell model

Cited by 37 publications

References 49 publications

Studying the gender effect on apparent mass during whole-body vibration using ANN

Studying the gender effect on apparent mass during whole-body vibration using ANN

FPGA to study the behavior of a maneuvering UGV using sliding innovation filter

Implementation of a Novel Tabu Search Optimization Algorithm to Extract Parasitic Parameters of Solar Panel

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