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Nanoparticles have gained recognition for significantly improving convective heat transfer efficiency near boundary layer flows. The characteristics of both momentum and thermal boundary layers are significantly influenced by the Prandtl number, which holds a crucial role. In this vein, the current study conducted a detailed computational analysis of the mixed convection flow of |$\gamma$| Al |$_2$| O |$_3$| -H |$_2$| O and |$\gamma$| Al |$_2$| O |$_3$| -C |$_2$| H |$_6$| O |$_2$| nanofluids over a stretching surface. This research integrates an effective Prandtl number, utilizing viscosity and thermal conductivity models based on empirical findings. Additionally, a unique double-fractional constitutive model is debuted to accurately evaluate the effective Prandtl number's function in the boundary layer. The equations were solved using a numerical technique that combined the finite-difference method with the L |$_1$| algorithm. This investigation presents numerical findings related to the velocity, temperature distributions, wall shear stress coefficient, and heat transfer coefficient, contrasting scenarios with and without the effective Prandtl number. The research shows that integrating nanoparticles into the base fluids reduces the temperature of the nanofluid with an effective Prandtl number while enhancing the heat transfer rate irrespective of its presence. Nonetheless, the introduction of a fractional parameter reduced the heat transfer efficiency within the system. Notably, the |$\gamma$| Al |$_2$| O |$_3$| -C |$_2$| H |$_6$| O |$_2$| nanofluid demonstrates superior heat transfer enhancement capabilities compared to its |$\gamma$| Al |$_2$| O |$_3$| -H |$_2$| O counterpart but also exacerbates the drag coefficient more significantly. Many practical applications of this study include electronics cooling, industrial process heat exchangers, and rotating and stationary gas turbines in power plants, and efficient heat exchangers in aircraft. [ABSTRACT FROM AUTHOR]

In the present study, for the first time the machine learning (ML) based refractive index (n) approach is established depends on the density (ρ) parameter of glasses for a dataset of 2000 oxide glasses to predict refractive index of B2O3-CaO-Li2O-Sb2O3 glasses. Density of the investigated glasses varied from 2.56 to 2.97 gm/cm3. The corresponding refractive index was changed from 2.540 to 2.405. The refractive index prediction based on density parameter derived from the density of glasses and constant 'K'. For all M-L techniques including gradient descent (GD), artificial neural network (ANN), and random forest regression (RFR), the density factor is used as an independent variable and the experimental refractive index as a dependent variable. The data set of 10,000 oxide glass samples was employed to forecast density using a variety of machine learning approaches. In comparison to other models, the Random forest regression (RFR) model fitted the glass data with the highest R2 value of 0.949 for refractive index prediction and 0.925 for density prediction. For both the prediction of density and refractive index, the R2 is controlled to 0.932 and 0.9223, respectively. The highest R2 values for refractive index and density prediction were gained when the tanh activation function was used in an artificial neural network (ANN) with varied activation functions. [ABSTRACT FROM AUTHOR]

In the evaluation of a Photovoltaic (PV) system's performance, precise calculation of the system's parameters is essential, as these parameters significantly influence its efficiency across various sunlight intensities, temperature ranges, and distinct load conditions. Addressing the intricate non-linear optimization problem of pinpointing these PV system parameters, the current research adopts a novel metaheuristic optimization approach, called Transit Search (TS). The proposed technique was rigorously tested on a monocrystalline solar panel, which included both single and double-diode model structures. The design of the objective function within this framework aims to diminish the square root of the average squared discrepancies between theoretical and measured current outputs, while remaining within the established parameter bounds. The proficiency of the TS algorithm was highlighted by employing a variety of statistical error indicators, underlining the latter's effectiveness. When pitted against other established optimization algorithms through comparative analysis, TS demonstrated outstanding capabilities, evidently outperforming its contemporaries in the accurate determination of PV system parameters. [ABSTRACT FROM AUTHOR]

In this study, the role of TiO2 on the physica, and optical properties as well as the γ-ray protection features of a set of six glass samples with the chemical formula (65-X)B2O3–15BaO–5Bi2O3–15ZnO–XTiO2, where X = 0–10 mol% in the step of 2% have been investigated. The density (ρ) increased gradually from 3.70 to 3.93 g/cm3 and the molar volume (Vm) reduced from 27.71 to 26.72 cm3/mol as the TiO2 content increased from 0 to 10 mol%. By the inclusion of TiO2 in the glass networks, some absorption bands in the ultraviolet and visible regions are formed. Values of the indirect optical band gaps (Eg) were 2.550, 2.510, 2.470, 2.370, 2.270, and 2.180 eV for Ti-0.0, Ti-2.0, Ti-4.0, Ti-6.0, Ti-8.0, and Ti-10.0 glasses, respectively. The linear refractive index (n0) calculated values varied from 2.515 to 2.631. The linear-attenuation coefficient ( μ) followed the order: Ti-0.0 < Ti-2.0 < Ti-4.0 < Ti-6.0 < Ti-8.0 < Ti-10.0. The sample coded as Ti-10.0 glass sample (highest content of TiO2) has the lowest half (HVL) and tenth (TVL) value layer. Within the investigated energy range of within the range: 51.590–19.480, 50.676–19.722, 50.696–19.833, 50.271–20.012, 49.860–20.193, and 49.460–20.376 for the prepared samples Ti-0.0, Ti-2.0, Ti-4.0, Ti-6.0, Ti-8.0, and Ti-10.0 glasses, respectively. Results confirmed that the suggested titanium bismo-borate glasses can be used in the optical field and as alternative materials for radiation shielding applications. [ABSTRACT FROM AUTHOR]

The melt-quenching method was used to manufacture newly synthesized glasses with a nominal composition of 60B2O3 – 20CaO – 15ZnO – 5Li2O – xEu2O3: 0 (Eu-0.0) ≤ x ≤ 0.5 (Eu-0.5) mol%. The structural, physical, FTIR, UV–visible spectra, and mechanical properties of the synthesized Eu-x glasses are examined. XRD results verified the amorphous condition of proposed glasses. The density (ρ) of the prepared glasses increased from 3.231 to 3.338 g cm−3, but in contrast, the molar volume (VM) decreased from 20.643 to 20.506 cm3 mol−1 with increasing Eu3+ ions. FTIR spectroscopy illustrated absorbance peaks appear around 393 and 464 nm, which indicates the presence of electronic states in the wide band gap of glass matrix. These peaks are attributed to the 5L6 and 5D2 electronic states of Eu3+ ions. UV–visible measurements showed an improvement in optical absorbance and a decrease in optical energy gap. The Eu3+ ions mol% doping into the proposed glasses results in generating photoluminescence glasses, which is attributed to the 5D0 → 7F1, 5D0 → 7F2, 5D0 → 7F3, and 5D0 → 7F4 electronic transitions of Eu3+ ions. Thus, the emission spectra due to the 393 nm excitation results in the appearance of emission peaks at 593 (orange), 617 (strong red), 653 (red), and 698 (red) nm. The Poisson's ratio (σ) of Eu-x glasses is decreased from 0.3927 to 0.3903 as the molar fraction of Eu3+ ions is increased from 0.0 to 0.5 mol%. The thermodynamic properties of the glassy network are hidden in the Gibbs free energy (G) which started at 33.56 and ended at 33.72 kJ.cm−3 at low and high Eu3+ ions content mol%. Furthermore, all elastic moduli increased linearly with molar increment of Eu3+ ions in the molecular structure of the proposed glassy network. [ABSTRACT FROM AUTHOR]

The parameters of a Photovoltaic (PV) model are pivotal in gauging its efficiency under varying sunlight irradiances, temperatures, and different load scenarios. Determining these PV model parameters poses a complex non-linear optimization challenge. This study is based on a new metaheuristic optimization algorithm called the Pelican Optimization Algorithm (POA) to discern the unknown parameters of the PV model. The suggested POA algorithm underwent testing using a monocrystalline panel, encompassing its single-diode configuration. The objective function is designed to minimize the root of the mean squared errors between the predicted and actual current values, adhering to specific parameter constraints. Various statistical error metrics were utilized to emphasize the performance of the proposed algorithm. A comparative analysis with other well-established algorithms was conducted, indicating that POA stands out as highly competitive since it showcases superior efficiency in parameter identification compared to its counterparts. [ABSTRACT FROM AUTHOR]

Four glasses of cadmium lead-borate glasses with nominal compositions of (75-X)B2O3–XPbO–5Na2O–10CdO–10ZnO: X = 5 (BPNCZPb-5), 10 (BPNCZPb-10), 15 (BPNCZPb-15), and 20 (BPNCZPb-20) mol% were fabricated using the well-known melt quenching route.The role of B2O3/PbO substitution on the physical properties and γ-ray shielding factors have been evaluated via MCNP simulation code and PhX software in the γ-energy range of 0.015: 15 MeV. The density (ρ) and molar volume (Vm) of the examined glasses grows systematically from 4.82 to 5.664 g/cm3 and from 18.88 to 22.02 cm3/mol as the PbO content increases from 5 to 20 mol% in the glass network. The oxygen molar volume (OMV) increased following the observation of an opposing the oxygen packing density (OPD) trend. The obtained values of simulated linear-absorption coefficient (µ) were in decent agreement with the values calculated by PhX software with a maximum relative differences, φ = of 4.497%. The simulated µ values drop from 127.981 to 0.130 cm−1 for BPNCZPb-5, from 189.241 to 0.158 cm−1 for BPNCZPb-10, from 243.308 to 0.180 cm−1 for BPNCZPb-15, and from 299.755 to 0.206 cm−1 for BPNCZPb-20 at photon energy range from 0.015: 15 MeV. At 0.5, 5, and 10 MeV, the µ of the BPNCZPb-X glasses have higher values than those of concretes. The BPNCZPb-20 glass sample possessed the lowest half- (HVL) and tenth- (TVL) value layers. The radiation protection efficiency (RPE) values reduced from ≈ 100.000% at 0.015 for all BPNCZPb-X glass samples to 6.305% (BPNCZPb-5), 7.587% (BPNCZPb-10), 8.626% (BPNCZPb-15), and 9.777% (BPNCZPb-20), respectively at gamma-ray energy 15 MeV. Results confirm that the suggested samples can be applied as alternative materials for radiation safety applications. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the major threats that attack women around the world. Its detection and diagnosis in the early stages can greatly improve care efficiency and reduce mortality rate. Early detection of breast cancer allows medical professionals to use less intrusive treatments, such as lumpectomies or targeted medicines, improving survival rates and lowering morbidity. This study developed a breast cancer segmentation system based on an improved version of the U-Net 3+ neural network. Various optimizations were applied to this architecture to improve the localization and segmentation performance. An evaluation of different state-of-the-art networks was performed to improve the performance of the proposed breast cancer diagnosis system. Various experiments were carried out on the INbreast Full-Field Digital Mammographic dataset (INbreast FFDM). The results obtained demonstrated that the proposed model achieved a dice score of 98.47%, which is a new state-of-the-art segmentation finding, showcasing its efficiency in detecting breast cancer from mammography images with the possibility of implementation for real applications. [ABSTRACT FROM AUTHOR]

Photo-catalyst nanoparticles (NPs) find applications in many diverse fields, including environmental remediation, energy conversion, and organic synthesis. By optimizing the nanoparticle's composition, size, morphology, and surface properties, the photo-catalytic performance can be enhanced to develop more efficient and sustainable catalytic systems. This work aligns with this innovative approach and aims to improve the photo-catalytic degradation of Sulfamethoxazole (SMX) through the intensification of the photo-catalyst and the micro-reactor. ZnO-NPs were synthesized using the sol-gel method. Zinc Acetate (Z.A) and sodium hydroxide were used as precursor materials. The resulting ZnO-NPs were characterized for their structure and crystallinity using X-Ray Diffraction (XRD) and the photo-catalytic activity was assessed with a micro-structured polymer reactor. The degradation of SMX through photo-catalysis proceeds through several stages that involve coupled processes, such as the transportation of molecules and chemical reactions. To solve the mathematical equations governing the transport and photocatalytic reaction, COMSOL Multiphysics software was utilized. The characterization results demonstrate the excellent crystallinity and high purity of the synthesized ZnO-NPs, enabling the estimation of the average diameter of the NPs under different synthesis conditions. The grain growth is faster (3.5 hr) at higher temperatures (70, 80, and 90 °C), and slower (4 hr) at lower temperatures (50 and 60°C). The photo-catalytic degradation is significantly more efficient on 16 nm ZnO-NPs than 50 nm ZnO-NPs. At this size, the conversion rate reaches 96%, surpassing the performance of commercial ZnO-NPs, which only degrades 81% of SMX. The conversion rate obtained through simulation is slightly higher than that achieved in the experiments. However, this difference remains negligible, and overall, the model fits well with the experimental data. This validation of the chosen model confirms its reliability and accuracy. [ABSTRACT FROM AUTHOR]

In this work, the role of insertion cobalt(II) on the physical properties, dielectric spectroscopy, and photon attenuation parameters of the prepared glasses 25NaF-10ZnO-(65-x)B2O3-xCoO-0.6Y2O3: x = 0.0 (Co-0.0) ≤ x ≤ 0.5 (Co-0.5) mol% has been investigated. The amorphous state of samples verified via the XRD measurements. The density (ρ) ∈ [2.9824, 3.0058 g.cm−3]. The molar volume (Vm) ∈ [21.868, 21.715 cm3.mol−1] as an increase of CoO from 0.0 to 0.5 mol% in the glass network. Dielectric spectroscopy of borate glass loaded with varying cobalt content was investigated throughout frequency range from 50 to 5 MHz. The recorded dielectric constant at 3 kHz was enhanced from 14.4 to 17.8 by cobalt doping. The dependency of tangent loss (tan δ) for all investigated glasses on frequency is normal behavior with dielectric relaxation which is enhanced and shifted by cobalt doping. At the photon energy (E = 0.015 MeV), the mass-attenuation-coefficient (MAC) values were 10.192, 10.246, 10.300, 10.354, and 10.408 cm2/g for the samples Co-0.0, Co-0.1, Co-0.2, Co-0.30, Co-0.4, and Co-0.5, respectively. These MAC values are corresponding to as increment of 0.216 cm2/g between the low and high CoO contents presented in the glass samples. Values of half value layer (HVL) of all proposed specimens were more significant than that of RS-360 and RS-520 commercial glasses. Results confirmed that the suggested glasses are suitable for radiation attenuation. [ABSTRACT FROM AUTHOR]

In this study, a bald eagle optimizer (BEO) is used to get optimal parameters of the fractional-order proportional-integral-derivative (FOPID) controller for load frequency control (LFC). SinceBEOtakes only a very short time in finding the optimal solution, it is selected for designing the FOPID controller that improves the system stability and maintains the frequency within a satisfactory range at different loads. Simulations and demonstrations are carried out using MATLAB-R2020b. The performance of the BEOFOPID controller is evaluated using a two-zone interlinked power system at different loads and under uncertainty of wind and solar energies. The robustness of the BEO-FOPID controller is examined by testing its performance under varying system time constants. The results obtained by the BEOFOPID controller are compared with those obtained by BEO-PID and PID controllers based on recent metaheuristics optimization algorithms, namely the sine-cosine approach, Jaya approach, grey wolf optimizer, genetic algorithm, bacteria foraging optimizer, and equilibrium optimization algorithm. The results confirm that the BEO-FOPID controller obtains the finest result, with the lowest frequency deviation. The results also confirm that the BEOFOPID controller is stable and robust at different loads, under varying system time constants, and under uncertainty of wind and solar energies. [ABSTRACT FROM AUTHOR]

The electron firehose instabilities are among the most studied kinetic instabilities, especially in the context of space plasmas, whose dynamics is mainly controlled by collisionless waveâ€"particle interactions. This paper undertakes a comparative analysis of the aperiodic electron firehose instabilities excited either by the anisotropic temperature or by the electron counter-beaming populations. Two symmetric counter-beams provide an effective kinetic anisotropy similar to the temperature anisotropy of a single (nondrifting) population, with the temperature along the magnetic field direction larger than that in the perpendicular direction. Therefore, the counter-beaming plasma is susceptible to firehose-like instabilities (FIs), parallel and oblique branches. Here we focus on the oblique beaming FI, which is also aperiodic when the free energy is provided by symmetric counter-beams. Our results show that, for relative small drifts or beaming speeds (U), not exceeding the thermal speed (α), the aperiodic FIs exist in the same interval of wavenumbers and the same range of oblique angles (with respect to the magnetic field direction), but the growth rates of counter-beaming FI (CBFI) are always higher than those of temperature anisotropy FI (TAFI). For U / α > 1, however, another electrostatic two-stream instability is also predicted, which may have growth rates higher than those of CBFI, and may dominate in that case the dynamics. [ABSTRACT FROM AUTHOR]

Instability of an adaptive flux observer (AFO) in the regenerating mode at low frequencies is a great challenge of sensorless induction motor (SIM) drives. Zero observer feedback gains (OFGs) in the regenerating mode at low frequencies are the main reasons for moving the dominant zero of the speed estimators to the unstable region. OFGs should be appropriately selected to transfer the unstable dominant zero to the stable region. In this paper, genetic algorithm (GA) and particle swarm optimization (PSO) techniques were used to design the OFGs for a stable observer. A fair comparison of the dominant zero location between the two approaches using the optimized OFGs is presented under parameter deviation. Analytical results and the design procedure of the OFGs using the two approaches are presented under deviations of stator resistance and mutual inductance to guarantee a stable dominant zero in the regenerating mode of IM. The dominant zeros obtained by PSO had a superior location to that obtained by GA for both stator resistance and mutual inductance deviations. It was observed that one of the gains had an almost constant value over a wide range of parameter deviations. However, the value of the other gain was dependent on the deviation of machine parameters. The advantage of using PSO over GA is that the relation between the gain and parameter deviation can be represented by a deterministic and mostly linear relationship. Simulation and experimental work of the SIM drive are presented and evaluated under the optimized OFGs. [ABSTRACT FROM AUTHOR]

Boundary layer analysis is invoked to clarify the aspects of variable thermal conductivity and thermophoretic forces on a steady state of MHD micropolar fluid flow in the existence of a uniform transverse magnetic field along an isothermal horizontal plate. The micropolar pattern permits the rotational freedom degrees that lead to couple stresses and a non symmetric stress tensor. The initiated PDEs governing the case pattern are mutated into a non-dimensional system due to proper transformations. The transformed mathematical governing equations are solved by implementing a very potent computer algebra software MATLAB code. The plotted graphs analyzed the attitude of multiple physical aspects involving factors on the flow attitude of micropolar velocity and angular velocity and temperature. Through the involved factors, the couple stress, skin friction and Nusselt number are manifested and interpreted amply. A new outcome for drag force and heat gradient experienced by the key factors is portrayed. Augmentation in Ω results in the thermophoretic forces that encapsulate the mass transmission. The local Nusselt number strengthened as the thermal conductivity, heat absorption factors or wall suction velocity were improved, and weakened due to the existence of viscous dissipation or heat generation impacts. As a particular case, the governing field equations of a classical Newtonian liquid are given by dropping the micropolar parameter impacts. [ABSTRACT FROM AUTHOR]

Nowadays, multi-criteria decision-making (MCDM) methods are used widely in many fields of research and applications. Many studies have shown that MCDM approaches are effective in determining the optimal solution to a variety of symmetrical and asymmetrical problems with numerous parameters. This article investigates a novel approach using multi criteria decision making (MCDM) to optimize the parameters of static var compensator (SVC) and power system stabilizers (PSS). The proposed technique integrates similarity membership function reduction algorithm (SMFRA), removal effects of criteria (REC) and combined compromise solution (CoCoSo). In the first stage, (SMFRA) is employed to select the most dominant controller parameters in the optimization process. Secondly, the weights of the reduced parameters are computed based on (REC). Finally, (CoCoSo) method searches for the optimal setting parameters. A detailed sensitivity analysis is presented to evaluate the obtained results. It is found that the suggested integrated technique is time saving, easily implemented and of low computation burden, which can successfully be implemented to solve a wide range of issues, both comparable and dissimilar. [ABSTRACT FROM AUTHOR]

The ability of space plasmas to self-regulate through mechanisms involving self-generated fluctuations is a topic of high interest. This paper presents the results of a new advanced quasilinear (QL) approach for the instability of electromagnetic ion-cyclotron modes driven by the relative alpha-proton drift observed in solar wind. For an extended parametric analysis, the present QL approach includes also the effects of intrinsic anisotropic temperatures of these populations. The enhanced fluctuations contribute to an exchange of energy between proton and alpha particles, leading to important variations of the anisotropies, the proton-alpha drift and the temperature contrast. The results presented here can help understand the observational data, in particular, those revealing the local variations associated with the properties of protons and alpha particles as well as the spatial profiles in the expanding solar wind. [ABSTRACT FROM AUTHOR]

In this paper, firstly we introduce the notions of soft supra locally α -closed sets in soft supra topological spaces. We investigate the relationships with different types of subsets of soft supra topological spaces. Secondly, we introduce the notion of SSL- α C-continuous functions and a decomposition of soft supra continuity is obtained. [ABSTRACT FROM AUTHOR]

Groundwater (GW) quality evaluation includes a variety of biological, chemical and physical parameters. The fundamental problem with water quality assessment is the difficulty with which a large number of parameters are evaluated. If all criteria have been used to evaluate the quality of GW, then computational difficulty will certainly increase. In this paper, a new hybrid three-stage assessment approach based on Feature Extraction Algorithm (FEA), standard deviation (SD) and Complex Proportional Assessment Method (COPRAS) was proposed. In the first stage the redundant criteria for GW quality assessment is removed using FEA. Secondly, the weights of the reduct parameters are evaluated based on SD. Finally, GW sites are ranked using (COPRAS). Sixteen GW samples were gathered from several GW wells. The collected samples were investigated for 12 various physicochemical water quality criteria to evaluate GW quality. The results reveal that sulfates (SO4), nitrate (NO3), Fluorides (F), sodium (Na), and Escherichia coli (E. coli) are the main parameters for GW quality assessment. Furthermore, the optimal concentrations of physicochemical parameters: (SO4), (NO3), (F), (Na), and (E. coli) are 18.9(mg/L), 8.18(mg/L), 0.222(mg/L), 21(mg/L), 1.9(MPN/100mL), respectively, with 40 WQI.The suggested approach is compared to three MCDM methods to validate the performance of the proposed methodology. The assessment results gained by the FEA combined with COPRAS and SD significantly minimize computational difficulty, reasonable and accurate. The approach presented in this study improves the system for evaluating GW quality. [ABSTRACT FROM AUTHOR]

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Classification of volcanic rocks is a fundamental task in the geologic studies. Volcanic rocks are igneous rocks that cooled rapidly above the surface of the Earth's crust. They are classified according to their oxide chemical content. Furthermore, volcanic rocks can also be classified numerically by statistical means. But these methods are mostly dependent on human expert decision making and have a high cost. In this paper, a novel approach in the classification of volcanic rocks is proposed. This method is based on the rough set mathematical theory. The continuous data of the information system are firstly discretized using the information loss method. Secondly, the discretized decision table is reduced and the decision rule sets are extracted. The results are consistent with previous methods and show that the proposed method reduces time and calculation costs. [ABSTRACT FROM AUTHOR]

Autonomy is considered an important criterion that characterizes the performance of electric vehicles. It is represented by the distance that could be traveled by a fully electric vehicle which mainly depends on several parameters such as the vehicle model, type of battery, type of motor, etc. In this context, to improve the autonomy of electric vehicles, this paper represents an optimization study for the electric motor based on two contributions. The first devise an energy optimization algorithm to reduce the motor losses by calculation of the stator flux reference according to the electromagnetic torque and the rotation speed. The second is concerned with controller parameters adjustment using the Particle Swarm Optimization (PSO) technique to improve the efficacy and robustness of the drive. The performance of this strategy is evaluated in terms of torque, flux ripples, and transient response to step variations of the torque control. A comparative study of the designed PI controllers based on PSO with four other control algorithms and tuning methods is established in order to prove the efficiency of PI_PSO. The analysis, modeling, and simulation results are presented to verify the validity of the proposed overall optimization study. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive flux observer (AFO) method of sensorless induction motor (IM) drives. The AFO gains are designed to ensure accurate estimated speed, especially at very low frequencies in the regenerating mode of operation. Stability analysis of AFO with the designed gains is presented using the Lyapunov theory. These gains are calculated to be adaptively dependent on the IM variables and parameters. The observer gains play a significant role on the stability and precision of AFO in the regenerating mode. The influence of the machine parameters mismatch on the AFO stability with zero feedback gains as well as the proposed feedback gains is provided. The sensitivity to stator resistance is also analyzed. The complete sensorless IM drive with the proposed AFO is executed by both MATLAB/Simulink program, and also in the laboratory. Analytical and experimental results under various working conditions are provided to prove the effectiveness of the proposed AFO, especially at very low stator frequencies. [ABSTRACT FROM AUTHOR]

Aiming to improve the control performance in the switched reluctance (SR) motor drives, this paper presents a simple nonlinear mathematical model of SRM. The model depends on describing the characteristic data obtained from finite element analysis (FEA) in a simple parametric formula. An adaptive fuzzy logic PI controller is used with the suggested model in speed control drive system. The controller is designed based on Mamdani type with nine control rules along with Gaussian function memberships. The control technique is implemented and tested under different operating conditions as well as its results are compared with those of conventional PI controller. Both control schemes operate in pulse width modulation (PWM) control mode. The proposed adaptive fuzzy logic PI improves the motor speed performance in terms of tracking precision and travel time. [ABSTRACT FROM AUTHOR]