Range Of Parameter Variations Research Articles

Understanding rhizospheric microbial dynamics in gladiolus corms through quorum sensing and quorum quenching for disease control and growth promotion

Gladiolus, a widely cultivated cut flower known for its aesthetically pleasing multicoloured spikes, has earned significant commercial popularity. A comprehensive understanding of the rhizosphere bacterial community associated with gladiolus is imperative for revealing its potential benefits. Molecular characterization is considered an effective method to gain insights into the structural and functional aspects of microbial populations. The soil characteristics and bacterial communities in the rhizosphere are typically influenced by quorum sensing (QS) and quorum quenching (QQ) mechanisms. This study aims to explore the niceties and diversity of rhizospheric bacterial populations linked with gladiolus corms, with a specific focus on understanding the dynamics of QS and QQ mechanisms in their complex interactions. The isolation of bacterial strains was achieved through the serial dilution method on nutrient agar (NA) media. The identification of the isolates was accomplished by amplifying 16 S rRNA gene sequences via polymerase chain reaction (PCR) via the use of universal primers. Sequence analysis was conducted via BLAST on the National Center for Biotechnology Information (NCBI) database. The characteristics of the isolated bacteria were elucidated via biosensors. This study identified three QS strains and five QQ strains. A consortium of quenchers was formulated utilizing five strains that demonstrated efficacy in mitigating the impact of disease on gladiolus and fostering growth. Among the three treatments—Scale, Descale, and Descale and Cut Half (DSC)—the DSC treatment emerged as the most effective. This treatment exhibited a broader range of variation in biological parameters over time, aligning with prevailing trends in the local market.

Assessment of variability for biochemical and mineral contents in fenugreek germplasm

Thirty accessions of fenugreek (Trigonellafoenum-graecumL.) were investigated for the morphological and proximate composition of (moisture, protein, phenols, total antioxidants and mineral contents) during 2022-2023 and 2023-2024. The genotypes showed a wide range of variations in the biochemical parameters. The fully mature leaves of fenugreek germplasm were subjected to biochemical analysis and revealed a wide range of variability in biochemical traits viz. Protein (3.19 to 5.57%) ascorbic acid content (31.8 to 82.5 ug/ g-1), phenol content (0.74 to 2.74 mg GAE g-1) and total antioxidants capacity (0.60 to 5.11 mg Trolox/g). EC 510685 was identified for green- copper color leaf with high antioxidant content of leaves ((5.11 mM Trolox/g), EC510717 was found rich in protein (5.5 %) and Zn content (1.12 mg/100 gm).EC510559 was reported to have higher Ca content (360mg100g-1) while EC510579 was observed with a higher test weight (20.15g). Significant differences were also recorded in mineral content viz. Ca (105 to 360mg/100 gm), Zn (0.34 to 1.2mg/100 gm) and mg (45.7 to 131mg/100 gm). Based on the evaluation superior genotypes identified can be exploited either for the promotion of antioxidants rich fenugreek, coloured leaves genotype for ornamental purposes and minerals-rich genotypes in the processing industry for fortification of fenugreek by developing products with other functional food to overcome malnutrition. This information could also be used to develop antioxidant-rich varieties through a suitable breeding approach.

Prediction of perceived annoyance caused by an electric drone noise through its technical, operational, and psychoacoustic parameters.

Electric drones serve diverse functions, including delivery and surveillance. Nonetheless, they encounter significant challenges due to their annoying noise emissions. To address this issue, a sound database was created from experiments conducted in a hover-test-bench and real flights operated indoors. These experiments involved a wide range of parameter variations and operational conditions. A global digital user study involving 578 participants was conducted to assess drone noise annoyance. Furthermore, correlations between annoyance levels, psychoacoustic metrics, sociocultural factors, and technical/operational parameters were analyzed. The effects of implementing acoustic optimization modifications on the drone's performance were quantified with a conceptual design tool. The findings indicate that reducing the levels of loudness, sharpness, tonality, and roughness or fluctuation strength led to an improvement in annoyance. Differences in variable importance of psychoacoustic metrics dependent on the specific model were found. Sociocultural factors did not affect annoyance. Technical and operational parameters impacted annoyance, especially when reducing blade tip speed. A 20% reduction in tip speed showed potential through tool application as it maintained acceptable drone performance while beneficially targeting annoyance. A multi-disciplinary optimization is recommended to maintain operational efficiency. Last, psychoacoustic metrics were validated as an effective measure to evaluate a design solution.

FEA-based pole arc optimization and sensitivity analysis of 8/6 SRM for EV application

The optimization of the pole arcs and sensitivity analysis of a 4-phase 8/6 Switched Reluctance Motor (SRM) using the Finite Element Analysis (FEA) technique for the Electric Vehicle (EV) application is presented in this article. The motor's power rating is estimated from the tractive force of an e-rickshaw(3-wheeler). Optimizing the pole arc in SRMs is essential for obtaining an optimal balance of performance, efficiency, and operating smoothness. This makes it a vital part of SRM design. The motor performance is analyzed by fixing the stator pole arc while varying the rotor pole arc and vice versa. The main performance attributes like torque, torque ripple, torque per rotor volume, and efficiency of an 8/6 SRM with various pole arc values are examined using the transient FEA method. A sensitivity analysis is conducted to evaluate the range of variation in the performance parameters of the motor when the pole arcs vary. Various performance indices, such as torque, torque ripple (TR), efficiency, and Torque Per Volume (TPV), are considered for the analysis. The sensitivity analysis is carried out based on the transient analysis. Finally, based on the findings, the optimal combination of pole arcs is determined and analyzed the performance using the FEA method. An electromagnetic design tool called Infolytica MOTORSOLVE is used to construct the FEA models and extract the characteristics.

Neural algorithm for optimization of multidimensional object controller parameters

Optimal control of multivariable systems is a complex dynamic process that minimizes the cost function to obtain the optimal control strategy. Unfortunately, for nonlinear systems, it is not possible to use the traditional linear quadratic regulator (LQR), which would be optimal over the entire range of parameter variation. The problem of nonlinear multivariable systems and their optimal control is very momentous. The solution presented in this paper is based on the application of Reinforcement Learning (RL) networks in controlling a five-degree-of-freedom overhead crane system. Additionally, unlike the classical approach, the algorithm is adapted to directly analyze tabular data of inputs and outputs of the controlled model instead of analyzing its state as feedback (model-free). Implementing the new control structure for the multivariable system improved control quality compared to the classical LQR controller with linearization at the operating point. In addition to quality, the resource indicators, which in the LQR controller are represented by the matrix R, have been significantly improved. The architecture of the neural control system is presented, ensuring that over the entire range of nonlinearity, the quality of control is preserved while reducing the cost of its resource intensity. Obtaining optimal control with reduced resources for its implementation induces a wide range of applications of such neural control in engineering systems. The effectiveness of the proposed control system has been demonstrated in simulation studies. The simulation results present the system’s excellent control performance and adaptability over the entire range of object nonlinearity. The neural algorithm resulted in significantly shorter adjustment time and better control quality with significantly less system resource consumption and increased system dynamics.

POD–ANN as digital twins for surge line thermal stratification

This paper describes a hybrid proper orthogonal decomposition (POD) and artificial neural network (ANN) strategy to construct digital twins of a pressurizer surge line under thermal stratification conditions. The one-way coupled conjugate heat transfer and thermal stress analysis was conducted by use of parametric modeling and the introduction of the inverse distance weighted interpolation for the grid mapping, which allows for the mapped grids to have the same number of nodes regardless of variations of surge line geometries. A snapshot-based POD was utilized to obtain truncated lower-order modes and the full-order system response was projected onto these modes with reduced state coefficients. Then the ANN was employed to establish a surrogate model between the five chosen design variables of interest and the reduced state coefficients, resulting in a surrogate-assisted digital twin for a pressurizer surge line. Prediction of fluid–structure interface temperature and thermal stress distribution was thus achieved in an in-line real-time manner for a wide range of parameter variations. We publicly share all code implementations, and we believe that our efforts open a door for the digital twining of thermo–fluid–structure interaction problems

Quantifying Biogeochemical Controls of Open Ocean CDOM From a Global Mechanistic Model

AbstractChromophoric dissolved organic matter (CDOM) is an important part of ocean carbon biogeochemistry with relevance to long‐term observations of ocean biology due to its dominant light absorption properties. Thus, understanding the underlying processes controlling CDOM distribution is important for predicting changes in light availability, primary production, and the cycling of biogeochemically important matter. We present a biogeochemical CDOM model for the open ocean with two classes of biological lability and uncertainty estimates derived from 43 ensemble members that provide a range of model parameter variations. Ensemble members were optimized to match global ocean in situ CDOM measurements and independently assessed against satellite CDOM estimates, which showed good agreement in spatial patterns. Based on the ensemble median, we estimate that about 7% of open‐ocean CDOM is of terrestrial origin, but the ensemble range is large (<0.1–26%). CDOM is rapidly removed in the surface ocean (<200 m) due to biological degradation for short‐lived CDOM and photodegradation for long‐lived CDOM, leading to a net flux of CDOM to the surface ocean from the dark ocean. This deep‐water source (ensemble median 0.001 m−1 yr−1) is similar in magnitude to the riverine flux (0.005 m−1 yr−1) into the surface ocean. Though discrepancies between the model and observational data remain, this work serves as a foundational framework for a mechanistic assessment of global CDOM distribution that is independent of satellite data.

Determining the effect of additional tank volume and air pressure in the spring on the dynamic indicators of a pneumatic system of spring suspension in high-speed railroad rolling stock

The object of this study is the pneumatic system in the spring suspension of rolling stock under conditions of high-speed movement from 170 to 250 km/h. Based on the thermodynamic model of the pneumatic spring suspension system, the influence of volume of the additional tank and the initial pressure in the pneumatic spring on the nature of change in the spring's dynamic stiffness, energy losses, and damping coefficient was studied. Based on the built "force-deformation" dependences for the pneumatic spring, it was established that the change in the volume of an additional tank has a slight effect on the deformation of the pneumatic spring at different speeds of the high-speed rolling stock. It was established that in the range of rolling stock speeds of 170–250 km/h, the diameter of the connecting pipeline is 30 mm, and the volume of the additional tank is from 30 to 60 l, the maximum change in the dynamic stiffness of the pneumatic spring up to 15.5 % occurs at the pressure in the spring of 6.5 bar. Dependences of energy loss and damping coefficient during the operating cycle of the pneumatic spring suspension system were derived. It was established that an increase in the volume of the additional tank and the initial pressure in the pneumatic spring leads to an increase in the energy loss during the operation cycle of the pneumatic system. The maximum values of the damping coefficient over the entire considered range of variable parameters are 1.16–1.29. It was established that with the volume of the additional tank in the range from 30 to 50 liters, the maximum values of the damping coefficient are observed at a diameter of the connecting pipeline of 25 mm and a speed of movement from 200 to 250 km/h. And with an additional tank volume of 60 liters – with a diameter of 30 mm and a speed of 170 to 250 km/h

Prediction models for building thermal mass of intermittently heated rooms for balancing energy consumption and indoor thermal comfort

Building thermal mass (BTM) plays an essential role in maintaining a comfortable indoor environment for intermittently heated rooms (IHR). However, how to properly determine the BTM in IHR is unclear for the comprehensive consideration of the opposite effects on the reduction of heating energy consumption (HEC) as well as the improvement of indoor thermal comfort (ITC). This study aims to investigate the comprehensive impact of BTM on the HEC and ITC of IHR in the hot summer and cold winter (HSCW) zone of China using the validated EnergyPlus model. The results indicate that BTM can significantly improve the ITC of IHR, whereas increase HEC. The degree of impact is mainly related to the internal wall heat accumulation coefficient, external wall insulation layer thermal resistance, and outdoor air mean temperature during non-heating periods. Response surface methodology is further employed to quantify the effects of BTM on HEC and ITC of IHR. Based on the predictive models, the range of parameter variations for BTM that simultaneously meet HEC and ITC requirements is obtained. The predictive models can provide a theoretical basis for balancing HEC and ITC in intermittently heated buildings in the HSCW zone of China.

Speed control of PM brushless DC motor using sensorless hybrid controller

In most industrial processes, rising productivity necessitates increased demand on electrical motors in order to minimize costs and improve drive system efficiency. The sensorless technique is preferred. Brushless DC (BLDC) motors compete with a wide range of different motor types in the motion control industry. The nonlinearity of BLDC motor characteristics is challenging to manage with a traditional proportional integral derivative (PID) controller. The PID controller's fuzzy logic allowed it to tune itself while operating online. Hybrid approaches outperform stand-alone algorithms because they can overcome their weaknesses without losing their advantage. The purpose of this study is to present a fuzzy PI+D controller that is simulated over a wide range of reference speeds, loads, and parameter variations. This paper presents a model of a sensorless BLDC motor with a speed controller. The responses of the rotor speed, electromagnetic torque, stator back electromotive force (EMF), and stator currents are effectively monitored. The findings from the simulation indicate that the hybrid controller presented in this study exhibits resilience to rapid load torque and parameter fluctuation. Furthermore, it demonstrates superior dynamic performance and exhibits notable enhancements in speed tracking and system stability. The performance of the system is enhanced through the utilization of the proposed hybrid intelligent controller.

Vertical spanning wall elastically restrained at the top: validation and parametric dynamic analysis

In unreinforced masonry structures, among the most dangerous events that can occur during earthquakes are the out-of-plane mechanisms. This type of response significantly changes if the wall is restrained by a horizontal element. The collapse, in this case, could take place for slipping/failure of the diaphragm connection or for overturning of the wall, following the formation of a crack at an intermediate height between the base and the top. A specific analytical model is used to capture the complex dynamic behavior of the wall, formed by two stacked rigid bodies (free to rock) with the top one connected to a flexible diaphragm. The model is calibrated using experimental data available in the literature and it is then used to carry out a dynamic parametric analysis. The variation range of relevant parameters refers to the building features surveyed in Emilia-Romagna region, Italy, and their effect on the global response of the system is investigated. Further, the influence of ground motion is considered, using different ground accelerations. The results of the analysis highlight that, for the considered area and return period, the maximum rotations of the system are significant only for large slenderness values. Further, the investigation shows that the diaphragm plays a crucial role in the dynamic response of the system. The stiffness of the diaphragm can significantly reduce the rotations and consequently the risk of overturning. Additionally, the study on the effect of the wall size pointed out how a top spring causes a reverse scale effect.

Effective Computational Model for Determining the Geometry of the Transition Zone of End Coils of Machined Springs, Enabling Efficient Use of the Spring Material.

This paper presents an analysis of the effect of the geometry of the end-coil transition zone on the material stress state of a machined compression spring with a rectangular wire cross-section. The literature relationships for determining the stresses in rectangular wire compression springs neglect the effects associated with the geometry of this zone. A series of non-linear numerical analyses were carried out for models of machined compression springs with a wide range of variation in geometrical parameters. The results of these analyses were used to develop a computational model to estimate the minimum value of the rounding radius ρmin, which ensures that the stresses in this zone are reduced to the level of the maximum coil stresses. The model is simple to apply, and allows the radius ρmin to be estimated for springs with a spring index between 2.5 and 10, a helix angle between 1° and 15°, and a proportion of the sides of the wire section between 0.4 and 5.

Research on quantitative inversion characterization of high-definition electrical imaging logging in oil-based mud based on backpropagation neural network and multiple population genetic algorithm-Levenberg-Marquardt algorithm

Electrical imaging logging in oil-based mud (OBM) has been developed for some time and is gradually playing an important role in the description of deep carbonate and shale reservoirs. Quantitative characterization of reservoir rock parameters such as resistivity is one of the most innovative developments in this field. The development of this technology needs to address and resolve four core issues: a wide range of parameter variations, removal of mud-cake influence in low-resistivity formations, dielectric rollover in high-resistivity formations, and multifrequency dielectric dispersion effects. To address the aforementioned issues, the joint use of a backpropagation neural network (BPNN) and the multiple population genetic algorithm (MPGA)-Levenberg-Marquardt (LM) algorithm for high-resolution quantitative imaging is developed. First, the numerical simulation is used to calculate the well-logging response data under the influence of multiple parameters, thereby establishing a forward response database. Then, within the forward response database, the instrument response function is fitted using BPNN, to compress the data volume. Next, based on the fitted response function, an inversion method for three parameters, including reservoir rock resistivity, permittivity, and plate standoff, is established using the LM algorithm optimized with MPGA. The results indicate that the use of a three-layer BPNN enables rapid and accurate calculation of the electrical imaging logging response in OBM. The calculation of a single point only requires 0.1 ms with an accuracy of more than 99%. The MPGA-LM algorithm exhibits stronger stability and improved inversion accuracy, with a single point inversion time of only 2 ms, and contributes to the high-definition quantitative description of electrical imaging logging in OBM, which is important in characterizing formation structures, distinguishing formation fractures, etc.

Probabilistic analysis of solid oxide fuel-cell integrated with gas turbine

Abstract Solid Oxide Fuel Cell (SOFC) integrated with a Gas Turbine (GT) is a highly efficient way to convert chemical energy of hydro carbon fuel into electrical energy. SOFC-GT is a high temperature, high pressure system and features a fuel flexibility, which makes it easier to retrofit into the existing power plants. A lot of research had already taken place to make SOFC-GT more fuel efficient and cost effective as well. SOFC-GT is a complex thermodynamic electro-chemical system that has numerous input variables that affect the overall efficiency of the system. In order to further develop the SOFC-GT technology and future research, clear understanding is required to analyze relationship between the input and output parameters. One way to analyze the input/output relationship over the range of parameter variations is to conduct a probabilistic sensitivity analysis. A probabilistic sensitivity analysis of 19 input variables has been conducted to understand how each variable would affect the net power output and overall efficiency of a SOFC-GT system.

Nutrient Dynamics in a Coupled Terrestrial Biosphere and Land Model (ELM‐FATES‐CNP)

AbstractWe present a representation of nitrogen and phosphorus cycling in the Functionally Assembled Terrestrial Ecosystem Simulator, a demographic vegetation model within the Energy Exascale Earth System land model. This representation is modular, and designed to allow testing of multiple hypothetical approaches for carbon‐nutrient coupling in plants. Novel model hypotheses introduced in this work include, (a) the controls on plant acquisition of aqueous mineralized nutrients in the soil and (b) fairly straight forward methods of allocating nutrients to specific plant organs and their losses through live plant turnover as well as litter fluxes generated through plant mortality. This combines the new with pre‐existing hypotheses (such as nitrogen fixation and soil decomposition) into a system that can accommodate plant‐soil dynamics for a large number of size‐ and functional‐type‐resolved plant cohorts within a time‐since‐disturbance‐resolved ecosystem. Root uptake of nutrients is governed by fine root biomass, and plants vary in their fine root biomass allocation in order to balance carbon and nutrient limitations to growth. We test the sensitivity of the model to a wide range of parameter variations and structural representations, and in the context of observations at Barro Colorado Island, Panama. A key model prediction is that plants in the high‐light‐availability canopy positions allocate more carbon to fine roots than plants in low‐light understory environments, given the widely different carbon versus nutrient constraints of these two niches within a given ecosystem. This model provides a basis for exploring carbon‐nutrient coupling with vegetation demography within Earth system models.

Linear stability of the viscous liquid flow in a channel with corrugated walls

Using the complete Navier-Stokes equations, we investigate the linear stability of a viscous flow in a channel with various corrugated walls. We consider both the longitudinal corrugations when the main flow has two velocity components and the transversely corrugated wall when the basic flow has one velocity component. In frame of one approach and in a wide range of variations in the corrugation parameters and shapes, we analyze the neutral curves for the linear stability problem. We calculate the critical Reynolds number above which the main flow is unstable and there are disturbances growing in time. Perturbations of the velocity and pressure fields are, in general, three-dimensional with two wave numbers. We solve numerically the generalized eigenvalue problem. In the case of the transversely corrugated wall, we obtain two regions of parameters where the dependencies of the critical Reynolds number on the corrugation parameters are qualitatively different. The limits of these regions depend only on the ratio of the amplitude and period of corrugations. In the case of the longitudinal-corrugations, we find the corrugation parameters where the basic flow is unstable with respect to the periodic disturbances with the same wavelength as the corrugations wavelength and undergoes “the unavoidable transition” to a flow with more complicated behaviour in time.

УСУНЕННЯ ЗАВАД У ДИНАМІЧНИХ СПЕКТРАХ ЗА НАЯВНОСТІ ПОТУЖНОГО СИГНАЛУ ЧАСТИНА 1. ПОТУЖНІ ШИРОКОСМУГОВІ ІМПУЛЬСИ ТА ЛІНІЙНО ЧАСТОТНО-МОДУЛЬОВАНІ ЗАВАДИ

Subject and Purpose. The writers aim at developing and testing a new method of interference mitigation, proceeding from the example of radio emissions from Jupiter. Its effectiveness is compared with the results of other workers, equally relating to the case of a significant overlapping, within the time-frequency window under analysis, of the areas occupied by the useful signal and the interference. Methods and Methodology. The analysis has revealed several fundamental limitations associated with the use of standard statis- tical methods for identifying sources of interference. A new approach is proposed that allows separating useful signals from inter- ference in the time-frequency plane. It is based on the idea of transferring the statistical analysis from the space of signal amplitudes to such of linear patterns which are formed by maximal readings while the spectrograms are being scanned in time, frequency or otherwise. Results. Methods of statistical data processing have been suggested which allow analysis of signals of a variety of power lev- els against the background of interference of comparable intensity. This enables a detailed analysis of the time-frequency patterns demonstrated by signals with a broad range of parameter variations. The algorithms developed demonstrate stability against changes in the interference background conditions that may be caused either by human activity or by natural factors, such as, e.g. ionospheric perturbations, changes in the frontend frequency response of a receiver resulting from a changed antenna beam orientation, or else from Faraday’s polarization plane rotation in the radio emission being received. Conclusions. The necessity of creating new interference mitigation techniques is stipulated both by worsening of the general level of interference at radio frequencies, and by the growth of complexity in the sporadically emerging time-frequency patterns that result from the improved time and frequency resolutions in the course of signal reception. A significant progress has been achieved, owing exclusively to the fundamental modifications of the signal processing algorithms that are based on varying the direction of analysis in the time-frequency plane.

Stability and reliability analysis of a non‐isolated high gain DC‐DC converter

AbstractThis paper investigates the stability and reliability analysis of a non‐isolated high‐gain DC‐DC converter. The proposed DC‐DC converter produces a high gain output voltage with a lower duty ratio and reduced voltage stress on the semiconductor switch. A reliability analysis is performed to predict the failure rate and lifetime of the individual components using the military handbook (MIL‐HDBK‐217F). A state space equation and small signal modeling of the proposed converter are derived to elucidate the performance of the proposed converter through stability analysis. A closed‐loop using PID controller is incorporated to attain the constant regulated output voltage during sudden parameter changes. The validation of the closed‐loop using the PID controller is verified with the wide range of variations in the different parameters, such as input voltage, load value, and reference voltage value. The laboratory‐based prototype is developed for the proposed converter and validated the performance with 250 W. The power density and efficiency of the proposed converter are 1.360 kW/L and 93%, respectively.

Influence of parameters of a piezoelectric nonlinear energy sink on targeted energy transfer characteristic

In the coupling system of elastic plate and piezoelectric nonlinear energy sink, the shunt circuit of piezoelectric material as a nonlinear energy sink (NES) is coupled with the main system, where the nonlinear stiffness and damping are realized by the shunt circuit of piezoelectric material. The targeted energy transfer (TET) characteristics of the system are analyzed by complexification-averaging method and harmonic balance method, the variation range of NES parameters is determined, and the slow invariant manifold, platform amplitude of the frequency responses, nonlinear normal modes and threshold interval of the system under different parameters are analyzed. The influences of piezoelectric NES parameters, such as mass ratio, damping and nonlinear stiffness, on the TET characteristics are obtained, and a general criterion for design of piezoelectric NES parameters is proposed.

Power stability control of wind-PV-battery AC microgrid based on two-parameters fuzzy VSG

Virtual synchronous generator (VSG) control addresses the issue of decreasing microgrid standby inertia caused by the rise in wind turbines and photovoltaic (PV) penetration. However, various types of perturbations occur frequently making the traditional constant parameter VSG control unable to meet the system performance requirements, and thus a two-parameters fuzzy VSG control is proposed to ensure that microgrid inertia and damping. Firstly, the device-level control of each generation unit in the microgrid is designed based on the wind-PV-battery alternating current (AC) microgrid architecture. Secondly, fuzzy VSG control uses fuzzy rules written in plain language to represent the relationship between the main VSG factors and the power and frequency. Then, the influence of virtual inertia and damping coefficient on the dynamic performance of the system is analyzed through the theory of small-signal model, and a reasonable variation range of VSG parameters are given. Finally, the simulation model of wind-PV-battery AC microgrid is built in MATLAB/Simulink, and compared with other improved VSG control strategies, the fuzzy VSG control proposed in this paper has better dynamic performance and safety stability. This research emphasizes the practicality and importance of utilizing fuzzy control to adjust VSG techniques for developing microgrid configurations incorporating more renewable energy sources to guarantee the reliability and efficiency of microgrid.