Variable Speed Research Articles

Phylo-Epigenetics in Phylogeny Analyses and Evolution.

Long-standing, continuous blurring and controversies in the field of phylogenetic interspecies relations, associated with insufficient explanations for dynamics and variability of speeds of evolution in mammals, hint at a crucial missing link. It has been suggested that transgenerational epigenetic inheritance and the concealed mechanisms behind play a distinct role in mammalian evolution. Here, a comprehensive sequence alignment approach in hominid species, i.e., Homo sapiens, Homo neanderthalensis, Denisovan human, Pan troglodytes, Pan paniscus, Gorilla gorilla, and Pongo pygmaeus, comprising conserved CpG islands of housekeeping genes, uncover evidence for a distinct variability of CpG dinucleotides. Applying solely these evolutionary consistent and inconsistent CpG sites in a classic phylogenetic analysis, calibrated by the divergence time point of the common chimpanzee (P. troglodytes) and the bonobo or pygmy chimpanzee (P. paniscus), a "phylo-epigenetic" tree has been generated, which precisely recapitulates branch points and branch lengths, i.e., divergence events and relations, as they have been broadly suggested in the current literature, based on comprehensive molecular phylogenomics and fossil records of many decades. It is suggested here that CpG dinucleotide changes at CpG islands are of superior importance for evolutionary developments. These changes are successfully inherited through the germ line, determining emerging methylation profiles, and they are a central component of transgenerational epigenetic inheritance. It is hidden in the DNA, what will happen on it later.

Improved Power Control Based Variable Speed Wind-Turbine DFIG under Hard Work Conditions: Application of Sliding Mode Theory

This paper introduces an efficient and simple power control for the Wind Energy Conversion System (WECS) based on the Doubly-Fed Induction Generator (DFIG). Due to the limitation performance of the conventional PI controller against DFIG parameters change and wind speed variation; the sliding mode theory is applied in order to overcome these drawbacks. To improve the performances of a WECS, robust and nonlinear control techniques, namely; Conventional Sliding Mode Control (C-SMC) and Third Order Sliding Mode Control (3O-SMC), were implemented to independently control the stator active and reactive powers. However, both techniques exhibited a chattering phenomenon, an undesirable phenomenon caused by discontinuous signals. To overcome this drawback and further enhance previous control techniques, an advanced Variable Gain Super Twisting Algorithm (VGSTA) is proposed and compared to SMC and 3O-SMC. Furthermore, to validate the effectiveness of the proposed VGSTA strategy in comparison to two previous control methods, the WECS was simulated and validates using the MATLAB/Simulink environment. The simulation results clearly demonstrated the superiority of the proposed VGSTA strategy over the previous SMC and 3O-SMC techniques. This was obvious in terms of both fast convergence velocity and reduce chattering phenomenon.

Market tempo: Decoding information speed across global stock markets

This study explores the speed of information absorption in global stock markets using the Damodaran model. Analysing daily stock returns from 2005 to 2015 across 25 countries and 26 indices, the research categorizes markets into major, OECD, and emerging types. Major markets demonstrate the fastest adjustment, achieving a remarkable 1-day speed, followed by OECD markets with a 2–4-day span and emerging markets showing a 2–6-day duration for full information absorption. The results highlight significant mean speed variations across these market categories, offering practical insights for international businesses, corporations, and mutual funds navigating financial transactions globally. This study contributes valuable insights into information absorption speed, emphasizing the hierarchy of major, OECD, and emerging markets based on their speediness. Limitations include the exclusive focus on daily stock returns and the absence of specific diagnostic statistics for the Damodaran model.

Effect of rotation speed fluctuation on rotor noise generation: A numerical and experimental study

The practical operations of rotors for unmanned aircraft systems can undergo time-varying rotation speeds due to various uncertainty factors. This work investigates the aeroacoustic effect of the rotor’s rotation speed fluctuation using both numerical and experimental approaches. The measured real-time angular speed signal reveals that a hovering rotor experiences highly deterministic rotation speed variations in one revolution, which are closely related to the motor property. Delayed detached eddy simulations are performed, and the fluctuating rotation speed is realized by controlling the mesh displacement at each time step. The results suggest that significant additional tones are produced at the excitation frequency and neighbour frequencies, even though the amplitudes of the rotation speed fluctuations at the dominant frequencies are much smaller than the mean rotation speed. By comparing the full signal to individual harmonic components, it is found that the phase difference between each mode is unimportant. Therefore, the total aeroacoustic effect can be regarded as a linear superposition of different harmonic components. Aeroacoustic source analysis is also performed to isolate the contribution of various source types and correlate the far-field noise with the near-field source distribution. The results show that the extra tonal noise is mostly dominated by the loading noise, with a weaker contribution from the thickness noise. The agreement between the experiments and the simulations indicates that the rotation speed fluctuation is likely responsible for the generation of middle-frequency tonal noise at harmonics of the blade passing frequency.

Asynchronous localization of dynamic node through underwater acoustic sensor networks

In most cases, the operation of underwater acoustic sensor networks (UASNs) relies on accurate sensor location information. However, UASNs present more challenges than terrestrial sensor networks, such as the propagation speed variation with depth (i.e., stratification effect), asynchronous clock, node mobility, etc. In this paper, an efficient method of asynchronous localization is proposed by taking into account the stratification effect and node mobility. Firstly, a network is constructed that consists of surface buoys, AUVs, and target sensors. Secondly, an iterative least squares (LS) method is developed to locate AUV by establishing the relationship between propagation delay and location estimation. Thirdly, the passive mobility velocity of AUV is used to develop and solve the mobility model of the target sensors. Then, with the support of AUV, an asynchronous localization method is developed to estimate the target position, which improves the localization accuracy through motion and stratification compensation strategies. Moreover, the proposed method is validated through Cramer Rao lower bound (CRLB) analysis. Finally, simulation is performed to show that the proposed method is more efficient in reducing the estimation errors.

Experimental optimization of the FSW parameters to weld the dissimilar Al- and Cu-alloys by using additives at their joints

Friction stir welding (FSW) stands as a promising technique for joining materials, offering advantages over conventional methods. This study investigates the influence of tool tilt angle, rotational speed and profile on welded joint characteristics using a design of experiment (DOE) approach. The research objective aims to determine optimal parameter combinations for improved mechanical properties. Methodology entails the systematic variation of tilt angle, rotational speed and tool profile in a DOE setup, with subsequent FSW of samples. Mechanical testing, including tensile, bend and hardness tests, is conducted on 24 samples, with scanning electron microscope (SEM) and microstructure analysis on two specimens. Results reveal that higher tilt angles, rotational speeds and threaded profiles yield increased tensile strength but decreased ductility. Similarly, bend tests show higher fracture loads but reduced deflection before fracture under these conditions. Hardness tests indicate elevated hardness in welded areas, with variations based on input parameters. Main findings highlight the importance of parameter optimization for desired mechanical properties. Lower tilt angles and rotational speeds promote smoother material flow and uniform heating, resulting in consistent microstructure and hardness distribution. In conclusion, this study provides valuable insights for optimizing FSW parameters to achieve desired mechanical properties in welded joints. The combination of a 2° tilt angle, threaded tool profile and 1500 rpm rotational speed demonstrated the highest tensile strength, while a 1° tilt angle, cylindrical tool profile and 1000 rpm rotational speed yielded highest ductility.

Nonlinear optimal frequency control for dynamic vibration absorber and its application

A principal limitation of passive dynamic vibration absorber (DVA) lies in its intrinsic design constraint, as it is tuned to a specific resonant frequency, rendering it less effective at mitigating vibrations over a variable frequency range. To ensure that the DVA retains its vibration reduction capability under loads with time-varying frequencies, this paper proposes a method for designing the optimal suspension frequency based on the external load frequency. The approach involves altering the stiffness of the DVA through semi-active or active control to achieve the optimal suspension frequency and the best vibration reduction performance. In this study, the ratio R between the optimal suspension frequency and the load frequency is defined, and the nonlinear characteristic of R, based on the lowest vibration transmission rate, is studied using a two degree-of-freedom DVA model. Furthermore, an optimal suspension frequency variation control strategy based on load frequency identification is presented. Combined with the typical load with time-varying frequency encountered in metro vehicles, a multi-body dynamics theoretical model and a rigid–flexible coupling dynamics model are established to verify the effectiveness of the nonlinear optimal frequency control. Finally, the full-size railway vehicle roller rig is used to verify the correctness of the principle of optimal frequency curve. The research results show that when the mass ratio is 0.1, compared with rigid suspension, the nonlinear optimal frequency control can reduce the root mean square (RMS) value of the carbody’s entire time period acceleration during variable speed operation by 62.2%, and the maximum RMS value is reduced by 83.6%. In nonlinear control, unlike passive DVA, the vibration is never higher than that of rigid suspension within a specific velocity range. Compared with linear control strategy, nonlinearity can further reduce the elastic vibration. The test results from roller rig indicate that the semi-active DVA can effectively reduce the elastic vibrations of the carbody, while also validating the correctness of the nonlinear optimal suspension frequency principle. Therefore, the nonlinear frequency control in this study can provide reference for structural vibration control under loads with time-varying frequencies.

Optimization of Controllable-Pitch Propeller Operations for Yangtze River Sailing Ships

The Yangtze River’s substantial variation in water depth and current speeds means that inland ships face diverse operational conditions within a single voyage. This paper discusses the adoption of controllable-pitch propellers, which adjust their pitch to adapt to varying navigational environments, thereby optimizing energy efficiency. We developed an optimization framework to determine the ideal pitch angle and rotation speed (RPM) under different sailing conditions. The energy performance model for inland ships was enhanced to account for the open-water efficiency of CPPs across various pitch angles and RPMs, considering the impacts of current and shallow water, among other factors. The optimization approach was refined by incorporating an improved genetic algorithm with an annealing algorithm to enhance the initial population, applying the K-means clustering algorithm for population segmentation, and using multi-parent crossover from diverse clusters. The efficacy of the optimization method for CPP operations was validated by analyzing three operational scenarios of a Yangtze sailing ship. Additionally, key components of the ship performance model were calibrated through experimental tests, demonstrating an anticipated fuel consumption reduction of approximately 5% compared to conventional fixed-pitch propellers.

Assessment of wind power potential and economic viability at Al-Hodeidah in Yemen: Supplying local communities with electricity using wind energy

Wind energy is a promising sector in the power generation industry because it is renewable and globally available. This study assessed the wind power potential and the economic viability of utilizing wind turbines at the chosen location to produce electricity. This work uses wind speed data collected during (2012–2014) at 10 m height. This research presents the maximum and mean values of measured wind speeds. We have analyzed annual, seasonal, and monthly variations of wind speed. The wind characteristics and wind power potential of the study site have been investigated using Weibull and Rayleigh distribution functions. The annual mean wind speed and Weibull parameters (shape and scale) have been determined to be 4.477 m/s, 2.494, and 5.046 m/s, respectively, according to the actual data collected over the three years. The annual mean power density and energy density have been computed to be 86.39 W/m2 and 757.226 kWh/m2 according to the actual data collected over the three years, and the predicted annual mean power density and energy density have been computed to be 86.492 W/m2 and 758.358 kWh/m2 using Weibull parameters and 164.372 W/m2 and 1441.2 kWh/m2 using Rayleigh distribution, respectively. Accordingly, the power density computed using the Weibull parameters was similar to the power density computed using real wind data, whereas the power density calculated by the Rayleigh function was higher. An economic analysis has been done to choose a suitable turbine for the study site. The results indicate that the wind turbine ZEFIR D14-Px-Ty is indeed a viable option for wind power generation in Al-Hodeidah. It has a relatively low cost of energy of $0.03/kWh and a high capacity factor of 0.428, indicating its efficiency in converting wind energy into electricity. Therefore, the selected location is recommended for some small stand-alone systems as well as small wind farms.

Comparison between junior and recreational based on internal and external load response in soccer

The characteristics of soccer games tend to be at medium and high intensity. Measurement of heart rate response and activity profile can be used to assess the physical condition performance of players in planning the right program. The purpose of this study was to analyze the differences between heart rate response and activity profile in junior and recreational soccer players. The sampling technique used was purposive sampling. 24 male soccer players (12 junior Aged 11.58 ± 0.28 Years, 142.25 ± 8.74 cm, 34.5 ± 6.42 kg) and (12 recreational Aged 32.7 ± 1.38 Years, 170.67 ± 3.92 cm, 73.42 ± 5.33 kg) underwent simulation game sessions of 15 minutes each recorded using Polar Verity Sense and Catapult One to capture internal and external load data. Data were analyzed using the Mann-Whitney U Test to determine the difference between the heart rate of junior and recreational players. The results showed that there was a significant difference between HRavg in junior players (166.1 ± 17.2) and recreation (155.3 ± 10.5) as well as HRmax in junior players (193.1 ± 12.3) and recreation (176.0 ± 10.0) (p < 0.05). In addition, in the variable top speed (6.20 ± 0.68) and also maximal acceleration (4.52 ± 0.39) there is a significant difference (p < 0.05). This study concludes that there is a significant difference in heart rate response, but in the activity profile only the top speed and maximal acceleration variables between soccer players. Keywords: heart rate response, activity profile, junior and recreational soccer players

Mechanisms of speed-accuracy trade-off in tennis topspin forehand of college players

ABSTRACT This study aimed to elucidate the mechanisms underlying the speed-accuracy relationship in a tennis topspin single-handed forehand groundstroke. Groundstrokes at three different speeds by nine college players were captured, with the variability of the ball landing position evaluated as indices of accuracy. Variabilities of ball launch variables (speed, launch angle, spin, etc.) and conversion ratios from these variabilities to the variability of the ball landing position were quantified. These variabilities and their conversion ratios could be influenced by different efforts exerted to generate ball speeds and different ball trajectories required to hit a target at each speed, respectively. The speed-accuracy trade-off was observed only in the hitting direction. While the variability of the spin axis increased, it had minimal influence on the ball landing position. Conversely, the conversion ratio in the hitting direction of the velocity elevation angle significantly increased, while its variability remained unchanged. Consequently, the geometrical requirements of ball trajectories can be responsible for the speed-accuracy trade-off. Therefore, even skilled players capable of maintaining consistent ball launch variables regardless of the shot speed should deliberately choose a moderately slower ball speed to avoid an inevitable increase in the variability of the ball landing position due to geometrical requirements.

Linear Active Disturbance Rejection Control System for the Travel Speed of an Electric Reel Sprinkling Irrigation Machine

The uniformity of the travel speed of electric reel sprinkling irrigation machines is a key factor affecting irrigation quality. However, conventional PID control is susceptible to sudden disturbances under complex farmland conditions, leading to reduced speed uniformity. To enhance the robustness of the control system, it is necessary to investigate new disturbance rejection control algorithms and their effects. Therefore, a kinematic model of the reel sprinkling irrigation machine and a brushless DC (BLDC) motor model were established, and a linear active disturbance rejection control (LADRC) strategy based on improved particle swarm optimization (IPSO) was proposed. The simulation results show that under variable speed conditions, the system exhibits no overshoot, with an adjustment time of 0.064 s; under variable load conditions, the speed vibration amplitude is less than 0.3%. The field test results indicate that at travel speeds of 10 m/h and 30 m/h, the maximum absolute deviation rate under IPSO-LADRC control is reduced by 27.07% and 13.98%, respectively, compared to PID control. The control strategy based on IPSO-LADRC effectively improves the control accuracy and robustness under complex farmland conditions, providing a reference for enhancing the control performance of other electric agricultural machinery.

Comparative analysis of offshore wind turbine blade maintenance: RL-based and classical strategies for sustainable approach

This study compares traditional methods like Corrective Maintenance (CM), Scheduled Maintenance (SM), and Condition-based Maintenance (CbM) with Reinforcement Learning (RL)-based offshore wind turbine (OWT) blade maintenance strategies. In order to address the dual challenge of minimizing carbon output while managing maintenance costs and operational efficiency, the study presents a mathematical model intended to estimate carbon emissions associated with OWT maintenance activities. The ability of the RL-based strategy to reduce the risk of fatigue failure in OWT blades and account for wind speed variability in maintenance schedule optimization is assessed. In order to provide a sustainable maintenance solution this strategy balances the trade-offs between economic profit and environmental effect. The findings demonstrate how RL can provide a balanced approach to maintenance that enhances both operational performance and environmental sustainability.

From Radar Sensor to Floating Car Data: Evaluating Speed Distribution Heterogeneity on Rural Road Segments Using Non-Parametric Similarity Measures

Rural roads, often characterized by winding paths and nearby settlements, feature frequent curvature changes, junctions, and closely spaced private accesses that lead to significant speed variations. These variations are typically represented by average speed or v85 profiles. This paper examines complete speed distributions along rural two-lane roads using Floating Car Data (FCD). The Wasserstein distance, a non-parametric similarity measure, is employed to compare speed distributions recorded by a radar Control Unit (CU) and a selected FCD sample. Initially, FCD speeds were validated against CU speeds. Subsequently, differences in speed distributions between the CU location and specific sections identified by sharp curves, intersections, or accesses have been assessed. The Wasserstein Distance is proposed as the most effective synthetic indicator of speed distribution variability along roadways, attributed to its metric properties. This measure offers a more concise and immediate assessment compared to an extensive array of statistical metrics, such as mean, median, mode, variance, percentiles, v85, interquartile range, kurtosis, and symmetry, as well as qualitative assessments derived from box plot trends.

A hybrid fuzzy logic-based MPPT algorithm for PMSG-based variable speed wind energy conversion system on a smart grid

Recently, wind power has gained popularity as a sustainable energy source. Wind energy conversion systems (WECSs) can accept fixed speed and variable speed (VS) operations. VS-WECSs are preferable to conventional WECSs because of their higher electricity collection capacity. Maximum power point tracking systems (MPPTs) are essential for maximizing the efficiency of wind energy generation in wind turbine installations linked to power grids. This study introduces a hybrid fuzzy logic controller-based MPPT (FLC-MPPT) for wind turbines (WTs) connected to permanent magnet synchronous generators (PMSGs) to accurately determine the maximum power output of WTs. This study employs a three-phase back-to-back converter to link a PMSG to a utility grid. The reference signals for pulse width modulation controllers comprise two-phase system currents. It constructs a converter that can transfer electrical energy in both directions using insulated-gate bipolar transistor technology and is powered by a battery. The machine-side converter uses model predictive control for the present control loop. Given the generator's susceptibility to changes in wind conditions, this factor is of the utmost importance. A WT simulation was conducted using MATLAB/Simulink and an FLC methodology was employed. The model used a PMSG. Measurements of rotor speed, power, induced voltage, and current were taken in relation to variations in wind speed. The simulation results show that the FLC-MPPT can maximize the output power over a wide range of wind speeds with a higher efficiency of 92.6% and performance of 95.7%.

New Fault Diagnosis Method for Rolling Bearings Based on Improved Residual Shrinkage Network Combined with Transfer Learning.

The fault diagnosis of rolling bearings is faced with the problem of a lack of fault data. Currently, fault diagnosis based on traditional convolutional neural networks decreases the diagnosis rate. In this paper, the developed adaptive residual shrinkage network model is combined with transfer learning to solve the above problems. The model is trained on the Case Western Reserve dataset, and then the trained model is migrated to a small-sample dataset with a scaled-down sample size and the Jiangnan University bearing dataset to conduct the experiments. The experimental results show that the proposed method can efficiently learn from small-sample datasets, improving the accuracy of the fault diagnosis of bearings under variable loads and variable speeds. The adaptive parameter-rectified linear unit is utilized to adapt the nonlinear transformation. When rolling bearings are in operation, noise production is inevitable. In this paper, soft thresholding and an attention mechanism are added to the model, which can effectively process vibration signals with strong noise. In this paper, the real noise is simulated by adding Gaussian white noise in migration task experiments on small-sample datasets. The experimental results show that the algorithm has noise resistance.

Decrease in muscle shortening and effect on strength and speed in adolescent soccer players (u-13)

In soccer, the variables of strength, speed and flexibility are associated with the athletic performance capacity of athletes, being these determinants not only to adapt to the demands of the competition, but at the same time flexibility can help to reduce the risk of injury. The aim of the study was to determine the effect on strength and speed after reducing muscle shortening. This is a quantitative study with an observational-analytical cross-sectional design. The evaluated sample consisted of 22 under-13 category players with an average age of 13.40±0.66 years, a height of 156.95±9.27 cm, and a body mass of 44.54±7.29 kg. They were randomly divided into a control group (n=10) and an experimental group (n=12). The experimental group underwent an 8-week intervention involving static stretches, incorporating the Proprioceptive Neuromuscular Facilitation method in the fourth week to decrease muscle shortening before the post-test. Knee extension and dorsiflexion were assessed using a goniometer, and physical abilities were measured through the My Jump Lab app, including Squat Jump, Counter Movement Jump, Counter Movement Jump with Arms, the Nordics hamstring test, and speed in 10, 20, and 30 meters using the Runmatic app. Significant results (p<0.05) were observed for jump height in Squat Jump, jump height, flight time, and speed in Counter Movement Jump, torque in the Nordics test, and speed in 30 meters. According to the findings of the present study it seems that flexibility influences vertical jumping ability and speed.

Simulation of ambient temperature and humidity distribution in eight-span greenhouse under different wind conditions and corn height

The greenhouse environment suitable for crop growth usually depends on reasonable ventilation, and outdoor air flow state and indoor crop height are important factors affecting the ventilation effect. This study conducted simulation and experimental research on corn cultivation in an eight-span plastic greenhouse, analyzing the effects of outdoor wind speed, wind direction, and indoor crop height variations on the uniformity of temperature and relative humidity distribution as well as the air flow dynamics within the greenhouse. The study shows that as outdoor wind speed increases from 0.5 m/s to 2.5 m/s, for every 1 m/s increment, temperatures decrease by 2.2 °C and 0.9 °C, respectively. The increase in outdoor wind speed resulted in uniformity of greenhouse temperature and humidity along the vertical height, but exacerbated the degree of inhomogeneity in the east-west direction. The change in outdoor wind direction leads to differences in airflow direction and ventilation volume. On the south side of the greenhouse, while temperature is lower, the relative humidity is higher, with maximum differences in temperature and humidity between the north and south sides being 0.6 °C and 1.5 %, respectively, when the northeast wind blows. The east wind has the best cooling effect. The uneven degree of temperature and humidity distribution in the east and west direction of the greenhouse is positively correlated with crop height. This study can provide valuable insights for adjusting and optimizing natural ventilation strategies in large multi-span greenhouses.

168 Real-world walking of people with the chronic lung disease COPD

Abstract Purpose Walking is crucial for active and healthy ageing, but it changes with age and in the presence of diverse health conditions, such as non-communicable diseases. In the field of the chronic lung disease COPD (chronic obstructive pulmonary disease), extensive research has been done on physical activity limitation, but little is known about the patterns of walking during daily life (i.e., real-world). We aimed to assess the levels and distribution of real-world walking (walking activity and gait parameters) in people with COPD compared with healthy adults, and across disease severity; and to identify domains of walking in COPD, using a single wearable device. Methods In a cross-sectional study, 550 people with COPD (37% women, with a mean (SD) age of 68 (8) years, postbronchodilator FEV1 54 (21) %) and 19 age-matched healthy adults were recruited in ten cities across eight countries. Subjects were given a single wearable device to wear at their lower back for one week. Twenty-five walking activity and gait parameters (e.g., number of steps, number of walking bouts (WB)>30s, walking speed in WB > 30s, cadence in WB > 30s, walking speed and cadence variability) were derived from the device outputs. Results Most walking activity and gait parameters were reduced in people with COPD compared to healthy adults, and according to COPD severity. Differences remained statistically significant after adjusting for age, sex, height and comorbidities in multivariable analyses. Factor analysis identified six distinct walking domains: Amount of walking, Patterns of walking, Pace, Rhythm, Pace variability and Rhythm variability. Conclusion Real-world walking in people with COPD is a multi-dimensional behaviour that is impaired as the disease progresses. These results may be used to set priorities and improve patient centricity in clinical practice, research and public health initiatives. Support/Funding Source This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No. 820820. This JU receives support from the European Union’s Horizon 2020 research and innovation programme and the European Federation of Pharmaceutical Industries and Associations (EFPIA).

Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

Induction motor drives with variable speed applications that employ vector control are quite popular nowadays because they provide strong dynamic performance and flexible speed control. By decoupling the torque-producing current components of stator current from the rotor flux, Indirect Field Oriented Control is recognized for generating excellent performance in induction motor drives. This investigation is being done to show the effectiveness of the novel FPI input-output data-trained ANFIS controller and compare the three controllers' performance in terms of load variation capabilities, motor parameter variation, and speed tracking. Consequently, a comparison of the three controllers is important to select which controller performs high in induction motor drive. Indirect Field Oriented Control of induction motor with Fractional Proportional Integral (FPI), Integer Proportional Integral (IPI), and Adaptive Neuro-Fuzzy Inference System (ANFIS) controllers are all discussed in this work along with their designs and comparative analysis. The square of error was used as a fitness function to genetically optimize the FPI and IPI controller parameters. The suggested Adaptive Neuro-Fuzzy Inference System (ANFIS) controller uses a hybrid learning approach. It is trained by the FPI controller's input-output data. Using the results of MATLAB simulations under various operating situations, the performance of the ANFIS controller was compared with FPI and IPI controllers. Because of FPI controller includes an extra parameter for adjustment, namely integration order, it performed better than IPI controller for speed control of the induction motor. According to the simulation findings, the percentage peak overshoots while employing ANFIS, FPI, and IPI controllers were 0.495 %, 12.062 %, and 14.699 % respectively. As a result, ANFIS exhibits a drastic reduction in overshoot. Additionally, with the ANFIS controlled induction motor drive, the speed achieves the required set value at 0.14 s. For no load, constant, and changing loads, the induction motor drive's performance has been examined.