The attenuation of the acoustic activity in marble specimens under uniaxial compressive loadingunloading loops is quantified in juxtaposition to that of the electric activity.In parallel,the existence of"pre-fail...The attenuation of the acoustic activity in marble specimens under uniaxial compressive loadingunloading loops is quantified in juxtaposition to that of the electric activity.In parallel,the existence of"pre-failure indiceso"warning about entrance into a critical stage,that of impending fracture,is explored.The acoustic activity is quantified in terms of the normalized number of acoustic hits,their average rate of production and their cumulative energy,and,the cumulative counts and their average rate of change.The electric activity is studied in terms of the pressure stimulated currents and the electric charge released.The analysis revealed that the acoustic and electric activities are linearly correlated to each other,suggesting that they are different manifestations of the same damage mechanisms.In addition,Kaiser's effect,governing the acoustic activity,is found to govern,also,the electric activity.Moreover,it is concluded that entrance into the critical stage is safely predicted by means of a simple criterion,based on the evolution of the average rate of change of the normalized cumulative counts in the natural time domain.These predictions are almost identical with those of the criterion based on the "varianceo" and the "entropies" of the time series of acoustic events in this domain.展开更多
In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent...In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.展开更多
Normally all real world process in a process industry will have time delay.For those processes with time delays,obtaining satisfactory closed loop performances becomes very difficult.In this work,three interacting cyl...Normally all real world process in a process industry will have time delay.For those processes with time delays,obtaining satisfactory closed loop performances becomes very difficult.In this work,three interacting cylindrical tank process is considered for study and the objective of the work is to compensate for time delays using smith predictor structure and to maintain the level in the third tank.Input/Output data is generated for the three interacting tank process.It is approximated as Integer First Order Plus Dead Time system(IFOPDT)and Fractional First Order Plus Dead Time system(FFOPDT).Smith predictor based fractional order Proportional Integral controller and Integer order Proportional Integral controller is designed for the IFOPDT and FFOPDT model using frequency response technique and their closed loop performance indices are compared and tabulated.The servo and regulatory responses are simulated using Matlab/Simulink.展开更多
The fourth-generation(4G)and fifth-generation(5G)wireless communication systems use the orthogonal frequency division multiplexing(OFDM)modulation techniques and subcarrier allocations.The OFDM modulator and demodulat...The fourth-generation(4G)and fifth-generation(5G)wireless communication systems use the orthogonal frequency division multiplexing(OFDM)modulation techniques and subcarrier allocations.The OFDM modulator and demodulator have inverse fast Fourier transform(IFFT)and fast Fourier transform(FFT)respectively.The biggest challenge in IFFT/FFT processor is the computation of imaginary and real values.CORDIC has been proved one of the best rotation algorithms for logarithmic,trigonometric,and complex calculations.The proposed work focuses on the OFDM transceiver hardware chip implementation,in which 8-point to 1024-point IFFT and FFT are used to compute the operations in transmitter and receiver respectively.The coordinate rotation digital computer(CORDIC)algorithm has read-only memory(ROM)-based architecture to store FFT twiddle factors and their angle generators.The address generation unit is required to fetch the data and write the results into the memory in the appropriate sequence.CORDIC provides low memory,delay,and optimized hardware on the field-programmable gate array(FPGA)in comparison to normal FFT architecture for the OFDM system.The comparative performance of the FFT and CORDICFFT based OFDM transceiver chip is estimated using FPGA parameters:slices,flip-flops,lookup table(LUTs),frequency,power,and delay.The design is developed using integrated synthesis environment(ISE)Xilinx version 14.7 software,synthesized using very-high-speed integrated circuit hardware description language(VHDL),and tested on Virtex-5 FPGA.展开更多
Permanent magnet brushless DC motors are used for various low-power applications,namely domestic fans,washing machines,mixer grinders and cooling fan applications.This paper focuses on selecting the best laminating ma...Permanent magnet brushless DC motors are used for various low-power applications,namely domestic fans,washing machines,mixer grinders and cooling fan applications.This paper focuses on selecting the best laminating material for the interior permanent magnet brushless DC(IPM BLDC)motor used in the cooling fan of automobiles.Various laminating materials,namely M19-29GA,M800-65A and M43,are tested using finite element analysis.The machine's vital performance metrics,namely the stator current,torque ripple,and hysteresis loss were analyzed in selecting the laminating material.The designed motor is also modelled as a mathematical model from the computed lumped parameters.The performance of the machines was validated through electromagnetic and thermal analysis.展开更多
In recent times,wind energy receives maximum attention and has become a significant green energy source globally.The wind turbine(WT)entered into several domains such as power electronics that are employed to assist t...In recent times,wind energy receives maximum attention and has become a significant green energy source globally.The wind turbine(WT)entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and grid.The turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power extraction.The pitch control angle is employed to effectively operate the WT at the above nominal wind speed.Besides,the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep WTs in a safe operating region.To achieve this,proportional–integral–derivative(PID)controllers are widely used and the choice of optimal parameters in the PID controllers needs to be properly selected.With this motivation,this paper designs an oppositional brain storm optimization(OBSO)based fractional order PID(FOPID)design for sustainable and secure energy in WT systems.The proposed model aims to effectually extract the maximum power point(MPPT)in the low range of weather conditions and save the WT in high wind regions by the use of pitch control.The OBSO algorithm is derived from the integration of oppositional based learning(OBL)concept with the traditional BSO algorithm in order to improve the convergence rate,which is then applied to effectively choose the parameters involved in the FOPID controller.The performance of the presented model is validated on the pitch control of a 5 MW WT and the results are examined under different dimensions.The simulation outcomes ensured the promising characteristics of the proposed model over the other methods.展开更多
Pocket Switched Networks(PSN)represent a particular remittent network for direct communication between the handheld mobile devices.Compared to traditional networks,there is no stable topology structure for PSN where t...Pocket Switched Networks(PSN)represent a particular remittent network for direct communication between the handheld mobile devices.Compared to traditional networks,there is no stable topology structure for PSN where the nodes observe the mobility model of human society.It is a kind of Delay Tolerant Networks(DTNs)that gives a description to circulate information among the network nodes by the way of taking the benefit of transferring nodes from one area to another.Considering its inception,there are several schemes for message routing in the infrastructure-less environment in which human mobility is only the best manner to exchange information.For routing messages,PSN uses different techniques such asDistributed Expectation-Based Spatio-Temporal(DEBT)Epidemic(DEBTE),DEBT Cluster(DEBTC),and DEBT Tree(DEBTT).Understanding on how the network environment is affected for these routing strategies are the main motivation of this research.In this paper,we have investigated the impact of network nodes,the message copies per transmission,and the overall carrying out of these routing protocols.ONE simulator was used to analyze those techniques on the basis of delivery,overhead,and latency.The result of this task demonstrates that for a particular simulation setting,DEBTE is the best PSN routing technique among all,against DEBTC and DEBTT.展开更多
Two novel improved variants of reptile search algorithm(RSA),RSA with opposition-based learning(ORSA)and hybrid ORSA with pattern search(ORSAPS),are proposed to determine the proportional,integral,and derivative(PID)c...Two novel improved variants of reptile search algorithm(RSA),RSA with opposition-based learning(ORSA)and hybrid ORSA with pattern search(ORSAPS),are proposed to determine the proportional,integral,and derivative(PID)controller parameters of an automatic voltage regulator(AVR)system using a novel objective function with augmented flexibility.In the proposed algorithms,the opposition-based learning technique improves the global search abilities of the original RSA algorithm,while the hybridization with the pattern search(PS)algorithm improves the local search abilities.Both algorithms are compared with the original RSA algorithm and have shown to be highly effective algorithms for tuning the PID controller parameters of an AVR system by getting superior results.Several analyses such as transient,stability,robustness,disturbance rejection,and trajectory tracking are conducted to test the performance of the proposed algorithms,which have validated the good promise of the proposed methods for controller designs.The performances of the proposed design approaches are also compared with the previously reported PID controller parameter tuning approaches to assess their success.It is shown that both proposed approaches obtain excellent and robust results among all compared ones.That is,with the adjustment of the weight factorα,which is introduced by the proposed objective function,for a system with high bandwitdh(α=1),the proposed ORSAPS-PID system has 2.08%more bandwidth than the proposed ORSA-PID system and 5.1%faster than the fastest algorithm from the literature.On the other hand,for a system where high phase and gain margins are desired(α=10),the proposed ORSA-PID system has 0.53%more phase margin and 2.18%more gain margin than the proposed ORSAPS-PID system and has 0.71%more phase margin and 2.25%more gain margin than the best performing algorithm from the literature.展开更多
Wireless sensor networks(WSNs)are characterized by their ability to monitor physical or chemical phenomena in a static or dynamic location by collecting data,and transmit it in a collaborative manner to one or more pr...Wireless sensor networks(WSNs)are characterized by their ability to monitor physical or chemical phenomena in a static or dynamic location by collecting data,and transmit it in a collaborative manner to one or more processing centers wirelessly using a routing protocol.Energy dissipation is one of the most challenging issues due to the limited power supply at the sensor node.All routing protocols are large consumers of energy,as they represent the main source of energy cost through data exchange operation.Clusterbased hierarchical routing algorithms are known for their good performance in energy conservation during active data exchange in WSNs.The most common of this type of protocol is the Low-Energy Adaptive Clustering Hierarchy(LEACH),which suffers from the problem of the pseudo-random selection of cluster head resulting in large power dissipation.This critical issue can be addressed by using an optimization algorithm to improve the LEACH cluster heads selection process,thus increasing the network lifespan.This paper proposes the LEACH-CHIO,a centralized cluster-based energyaware protocol based on the Coronavirus Herd Immunity Optimizer(CHIO)algorithm.CHIO is a newly emerging human-based optimization algorithm that is expected to achieve significant improvement in the LEACH cluster heads selection process.LEACH-CHIO is implemented and its performance is verified by simulating different wireless sensor network scenarios,which consist of a variable number of nodes ranging from 20 to 100.To evaluate the algorithm performances,three evaluation indicators have been examined,namely,power consumption,number of live nodes,and number of incoming packets.The simulation results demonstrated the superiority of the proposed protocol over basic LEACH protocol for the three indicators.展开更多
The development of non-linear loads at consumers has significantly impacted power supply systems.Since,the poor power quality has been found in the three-phase distribution system due to unbalanced loads,harmonic curre...The development of non-linear loads at consumers has significantly impacted power supply systems.Since,the poor power quality has been found in the three-phase distribution system due to unbalanced loads,harmonic current,undesired voltage regulation,and extreme reactive power demand.To overcome this issue,Distributed STATicCOMpensator(DSTATCOM)is implemented.DSTATCOM is a shunt-connected Voltage Source Converter(VSC)that has been utilized in distribution networks to balance the bus voltage in terms of enhancing reactive power control and power factor.DSTATCOM can provide both rapid and continuous capacitive and inductive mode compensation.A rectified resistive and inductive load eliminates current harmonics in a three-phase power supply.The synchronous fundamental DQ frame is a time-domain approach developed from three-phase system space vector transformations has been designed using MATLAB/Simulink.The DQ theory is used to produce the reference signal for the Pulse Width Modulation(PWM)generator.In addition,a traditional Propor-tional Integral Derivative(PID)controller is designed and compared with pro-posed soft computing approaches such as Fuzzy–PID and Artificial Neural Network(ANN-PID)and compared accurate reference current determination for Direct Current(DC)bus through DC link.An Analytical explores the pro-posed control strategies given to establish superior outcomes.Finally,total harmo-nic distortion analysis should be taken for performance analysis of the proposed system with IEEE standards.展开更多
Wireless sensor network(WSN)is a group of interconnected sensor nodes that work wirelessly to capture the information of surroundings.The routing of the network is a challenging task.The routing of WSN is classified a...Wireless sensor network(WSN)is a group of interconnected sensor nodes that work wirelessly to capture the information of surroundings.The routing of the network is a challenging task.The routing of WSN is classified as proactive,reactive,and hybrid.Adhoc on-demand distance vector(AODV)routing is an example of reactive routing based on the demand route formations among different nodes in the network.The research article emphasizes the design and simulation of the AODV routing hardware chip using very-high-speed integrated circuit hardware description language(VHDL)programming in Xilinx integrated synthesis environment(ISE)14.7 software.The performance of the chip is studied based on the field-programmable gate array(FPGA)hardware parameters such as slices,lookup table(LUTs),input/output block(IOB),flipflops,and memory for the different configurations of the network(N=10,20….100).The delay and frequency are also estimated on the Virtex-5 FPGA.The performance of the WSN with AODV routing is also analyzed based on the packet delivery ratio,throughput,delay,and control overhead.The simulation test cases verified the 8-bit,64-bit,and 128-bit data communication within the nodes.展开更多
This paper proposes a new peak current control switching(PCCS)method for single-phase inverter in photovoltaic(PV)generation system.This method minimizes the difference between a peak current and the current command w...This paper proposes a new peak current control switching(PCCS)method for single-phase inverter in photovoltaic(PV)generation system.This method minimizes the difference between a peak current and the current command with a constant switching frequency.In this paper,the principle and the simulation results of the proposed method are described.In this paper,the principle and the simulated transient characteristics of this PCCS method are described.From the results,it is clarified that the proposed switching method is effective.展开更多
The challenges that electric vehicles(EVs)must overcome today include the high cost of batteries,poor specific energy,and ineffectiveness in estimating the state of batteries using traditional methods.This article rev...The challenges that electric vehicles(EVs)must overcome today include the high cost of batteries,poor specific energy,and ineffectiveness in estimating the state of batteries using traditional methods.This article reviews(i)current research trends in EV technology according to the Web of Science database,(ii)current states of battery technology in EVs,(iii)advancements in battery technology,(iv)safety concerns with high-energy batteries and their environmental impacts,(v)modern algorithms to evaluate battery state,(vi)wireless charging technology and its practical limitations,(vii)key barriers to battery technology,and(viii)conclusions and recommendations are also provided.This paper examines energy-storage technologies for EVs,including lithium-ion,solid-state,and lithium-air batteries,fuel cells,and ultracapacitors.The core characteristics,advantages,disadvantages,and safety concerns associated with these batteries are discussed.Internet-of-Things(IoT)-based approaches are described to assess the battery state in real-time.Furthermore,for enhanced electric mobility,wireless power transfer charging techniques are discussed.Finally,recent advancements and potential outcomes for future EV technologies are outlined.展开更多
Subcutaneous vein network plays important roles to maintain microcirculation that is related to some diagnostic aspects.Despite developments of optical imaging technologies,still the difficulties about deep skin vascu...Subcutaneous vein network plays important roles to maintain microcirculation that is related to some diagnostic aspects.Despite developments of optical imaging technologies,still the difficulties about deep skin vascular imaging have been continued.On the other hand,since hemoglobin con-centration of human blood has key role in the veins imaging by optical manner,the used wavelength in vascular imaging,must be chosen considering absorption of hemoglobin.In this research,we constructed a near infrared(NIR)light source because of lower absorption of hemoglobin in this optical region.To obtain vascular image,reflectance geometry was used.Next,from recorded images,vascular network analysis,such as calculation of width of vascular of interest and complexity of selected region were implemented.By comparing with other modalities,we observed that proposed imaging system has great advantages including nonionized radiation,moderate penetration depth of 0.5-3 mm and diameter of 1 mm,cost-effective and algorit hmic simplicity for analysis.展开更多
Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost,gains,energy,mass,and so on.In order to solve optimization problems,metaheuristic algorithms are essential.Most of thes...Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost,gains,energy,mass,and so on.In order to solve optimization problems,metaheuristic algorithms are essential.Most of these techniques are influenced by collective knowledge and natural foraging.There is no such thing as the best or worst algorithm;instead,there are more effective algorithms for certain problems.Therefore,in this paper,a new improved variant of a recently proposed metaphorless Runge-Kutta Optimization(RKO)algorithm,called Improved Runge-Kutta Optimization(IRKO)algorithm,is suggested for solving optimization problems.The IRKO is formulated using the basic RKO and local escaping operator to enhance the diversification and intensification capability of the basic RKO version.The performance of the proposed IRKO algorithm is validated on 23 standard benchmark functions and three engineering constrained optimization problems.The outcomes of IRKO are compared with seven state-of-the-art algorithms,including the basic RKO algorithm.Compared to other algorithms,the recommended IRKO algorithm is superior in discovering the optimal results for all selected optimization problems.The runtime of IRKO is less than 0.5 s for most of the 23 benchmark problems and stands first for most of the selected problems,including real-world optimization problems.展开更多
Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control...Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control,navigation,route mapping,etc.The traffic prediction model aims to predict the traffic conditions based on the past traffic data.For more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis model.This study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALSTM)model for traffic prediction.The proposed OCNN-ALSTM technique primarily preprocesses the traffic data by the use of min-max normalization technique.Besides,OCNN-ALSTM technique was executed for classifying and predicting the traffic data in real time cases.For enhancing the predictive outcomes of the OCNN-ALSTM technique,the bird swarm algorithm(BSA)is employed to it and thereby overall efficacy of the network gets improved.The design of BSA for optimal hyperparameter tuning of the CNN-ALSTM model shows the novelty of the work.The experimental validation of the OCNNALSTM technique is performed using benchmark datasets and the results are examined under several aspects.The simulation results reported the enhanced outcomes of the OCNN-ALSTM model over the recent methods under several dimensions.展开更多
The design and analysis of a fuel cell vehi-cle-to-grid(FCV2G)system with a high voltage conver-sion interface is proposed.The system aims to maximize the utilization of fuel cell vehicles(FCVs)as distributed energy r...The design and analysis of a fuel cell vehi-cle-to-grid(FCV2G)system with a high voltage conver-sion interface is proposed.The system aims to maximize the utilization of fuel cell vehicles(FCVs)as distributed energy resources,allowing them to actively participate in the energy market.The proposed FCV2G system has FCVs,power electronics interfaces,and the electrical grid.The power electronics interfaces are responsible for con-verting the low-voltage output of the fuel cell stack into high-voltage DC power,and ensuring efficient power transfer between the FCVs and the grid.To optimize the operation of the FCV2G system,the momentum search algorithm(MSA)is employed.By applying MSA,the FCV2G system can achieve optimal power dispatch,con-sidering factors such as energy efficiency,grid stability,and economic feasibility.The proposed method is tested in MATLAB.The best MSA and dynamic load profile solu-tions are run for 24 h and the results show that 100%import of FCVs 51.0%more than 100%electric vehicle.Peak-cutting and vehicle-to-grid service revenue are 30.5%and 95.0%greater,respectively.Low discharge loss,high capacity,and high discharge power are the main advantages of FCVs.The benchmark FCVs ratio of 15%is used for sensitivity analysis.The findings reveal that the overall advantages of FCV2G are improved.Index Terms—Continuous conduction mode,DC-DC converter,discontinuous conduction mode,fuel cell vehi-cle,utility-grids,vehicle-to-grid.展开更多
This paper presents a new Double-E-Triple-H-Shaped NRI(negative refractive index)metamaterial(MM)for dual-band microwave sensing applications.Here,a horizontal H-shaped metal structure is enclosed by two face-to-face ...This paper presents a new Double-E-Triple-H-Shaped NRI(negative refractive index)metamaterial(MM)for dual-band microwave sensing applications.Here,a horizontal H-shaped metal structure is enclosed by two face-to-face E-shaped metal structures.This double-E-H-shaped design is also encased by two vertical H-shaped structures along with some copper links.Thus,the Double-E-Triple-H-Shaped configuration is developed.Two popular substrate materials of Rogers RO 3010 and FR-4 were adopted for analyzing the characteristics of the unit cell.The proposed structure exhibits transmission resonance inside the S-band with NRI and ENG(Epsilon Negative)metamaterial properties,and inside the C-band with ENG and MNG(Mu Negative)metamaterial properties.A good effective medium ratio(EMR)of 8.06 indicates the compactness and effectiveness of the proposed design.Further analysis has been done by changing the thickness of the substrate material as well and a significant change in the effective medium ratio is found.The validity of the proposed structure is confirmed by an equivalent circuit model.The simulated result agrees well with the calculated result.For exploring microwave sensing applications of the proposed unit cell,permittivity and pressure sensitivity performance were investigated in different simulation arrangements.The compact size,effective parameters,high sensitivity and a good EMR represent the proposed metamaterial as a promising solution for S-band and C-band microwave sensing applications.展开更多
In the era of digital signal processing,like graphics and computation systems,multiplication-accumulation is one of the prime operations.A MAC unit is a vital component of a digital system,like different Fast Fourier ...In the era of digital signal processing,like graphics and computation systems,multiplication-accumulation is one of the prime operations.A MAC unit is a vital component of a digital system,like different Fast Fourier Transform(FFT)algorithms,convolution,image processing algorithms,etcetera.In the domain of digital signal processing,the use of normalization architecture is very vast.The main objective of using normalization is to performcomparison and shift operations.In this research paper,an evolutionary approach for designing an optimized normalization algorithm is proposed using basic logical blocks such as Multiplexer,Adder etc.The proposed normalization algorithm is further used in designing an 8×8 bit Signed Floating-Point Multiply-Accumulate(SFMAC)architecture.Since the SFMAC can accept an 8-bit significand and a 3-bit exponent,the input to the said architecture can be somewhere between−(7.96872)_(10) to+(7.96872)_(10).The proposed architecture is designed and implemented using the Cadence Virtuoso using 90 and 130 nm technologies(in Generic Process Design Kit(GPDK)and Taiwan Semiconductor Manufacturing Company(TSMC),respectively).To reduce the power consumption of the proposed normalization architecture,techniques such as“block enabling”and“clock gating”are used rigorously.According to the analysis done on Cadence,the proposed architecture uses the least amount of power compared to its current predecessors.展开更多
Any nonlinear behavior of the system is analyzed by a useful way of Total Harmonic Distortion(THD)technique.Reduced THD achieves lower peak current,higher efficiency and longer equipment life span.Simulated annealing(S...Any nonlinear behavior of the system is analyzed by a useful way of Total Harmonic Distortion(THD)technique.Reduced THD achieves lower peak current,higher efficiency and longer equipment life span.Simulated annealing(SA)is applied due to the effectiveness of locating solutions that are close to ideal and to challenge large-scale combinatorial optimization for Permanent Magnet Synchronous Machine(PMSM).The parameters of direct torque controllers(DTC)for the drive are automatically adjusted by the optimization algorithm.Advantages of the PI-Fuzzy-SA algorithm are retained when used together.It also improves the rate of system convergence.Speed response improvement and har-monic reduction is achieved with SA-based DTC for PMSM.This mechanism is known to be faster than other algorithms.Also,it is observed that as compared to other algorithms,the projected algorithm yields a reduced total harmonic distor-tion.As a result of the employment of Space Vector Modulation(SVM)techni-que,the system is resistant to changes in motor specifications and load torque.Through MATLAB&Simulink simulation,the experiment is done and the per-formance is calculated for the controller.展开更多
文摘The attenuation of the acoustic activity in marble specimens under uniaxial compressive loadingunloading loops is quantified in juxtaposition to that of the electric activity.In parallel,the existence of"pre-failure indiceso"warning about entrance into a critical stage,that of impending fracture,is explored.The acoustic activity is quantified in terms of the normalized number of acoustic hits,their average rate of production and their cumulative energy,and,the cumulative counts and their average rate of change.The electric activity is studied in terms of the pressure stimulated currents and the electric charge released.The analysis revealed that the acoustic and electric activities are linearly correlated to each other,suggesting that they are different manifestations of the same damage mechanisms.In addition,Kaiser's effect,governing the acoustic activity,is found to govern,also,the electric activity.Moreover,it is concluded that entrance into the critical stage is safely predicted by means of a simple criterion,based on the evolution of the average rate of change of the normalized cumulative counts in the natural time domain.These predictions are almost identical with those of the criterion based on the "varianceo" and the "entropies" of the time series of acoustic events in this domain.
文摘In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.
文摘Normally all real world process in a process industry will have time delay.For those processes with time delays,obtaining satisfactory closed loop performances becomes very difficult.In this work,three interacting cylindrical tank process is considered for study and the objective of the work is to compensate for time delays using smith predictor structure and to maintain the level in the third tank.Input/Output data is generated for the three interacting tank process.It is approximated as Integer First Order Plus Dead Time system(IFOPDT)and Fractional First Order Plus Dead Time system(FFOPDT).Smith predictor based fractional order Proportional Integral controller and Integer order Proportional Integral controller is designed for the IFOPDT and FFOPDT model using frequency response technique and their closed loop performance indices are compared and tabulated.The servo and regulatory responses are simulated using Matlab/Simulink.
文摘The fourth-generation(4G)and fifth-generation(5G)wireless communication systems use the orthogonal frequency division multiplexing(OFDM)modulation techniques and subcarrier allocations.The OFDM modulator and demodulator have inverse fast Fourier transform(IFFT)and fast Fourier transform(FFT)respectively.The biggest challenge in IFFT/FFT processor is the computation of imaginary and real values.CORDIC has been proved one of the best rotation algorithms for logarithmic,trigonometric,and complex calculations.The proposed work focuses on the OFDM transceiver hardware chip implementation,in which 8-point to 1024-point IFFT and FFT are used to compute the operations in transmitter and receiver respectively.The coordinate rotation digital computer(CORDIC)algorithm has read-only memory(ROM)-based architecture to store FFT twiddle factors and their angle generators.The address generation unit is required to fetch the data and write the results into the memory in the appropriate sequence.CORDIC provides low memory,delay,and optimized hardware on the field-programmable gate array(FPGA)in comparison to normal FFT architecture for the OFDM system.The comparative performance of the FFT and CORDICFFT based OFDM transceiver chip is estimated using FPGA parameters:slices,flip-flops,lookup table(LUTs),frequency,power,and delay.The design is developed using integrated synthesis environment(ISE)Xilinx version 14.7 software,synthesized using very-high-speed integrated circuit hardware description language(VHDL),and tested on Virtex-5 FPGA.
文摘Permanent magnet brushless DC motors are used for various low-power applications,namely domestic fans,washing machines,mixer grinders and cooling fan applications.This paper focuses on selecting the best laminating material for the interior permanent magnet brushless DC(IPM BLDC)motor used in the cooling fan of automobiles.Various laminating materials,namely M19-29GA,M800-65A and M43,are tested using finite element analysis.The machine's vital performance metrics,namely the stator current,torque ripple,and hysteresis loss were analyzed in selecting the laminating material.The designed motor is also modelled as a mathematical model from the computed lumped parameters.The performance of the machines was validated through electromagnetic and thermal analysis.
基金Deputyship for Research and Innovation,Ministry of Education in Saudi Arabia,project number(IFPRC-040-135-2020)。
文摘In recent times,wind energy receives maximum attention and has become a significant green energy source globally.The wind turbine(WT)entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and grid.The turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power extraction.The pitch control angle is employed to effectively operate the WT at the above nominal wind speed.Besides,the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep WTs in a safe operating region.To achieve this,proportional–integral–derivative(PID)controllers are widely used and the choice of optimal parameters in the PID controllers needs to be properly selected.With this motivation,this paper designs an oppositional brain storm optimization(OBSO)based fractional order PID(FOPID)design for sustainable and secure energy in WT systems.The proposed model aims to effectually extract the maximum power point(MPPT)in the low range of weather conditions and save the WT in high wind regions by the use of pitch control.The OBSO algorithm is derived from the integration of oppositional based learning(OBL)concept with the traditional BSO algorithm in order to improve the convergence rate,which is then applied to effectively choose the parameters involved in the FOPID controller.The performance of the presented model is validated on the pitch control of a 5 MW WT and the results are examined under different dimensions.The simulation outcomes ensured the promising characteristics of the proposed model over the other methods.
基金UPNM Grant J0117-UPNM/2016/GPJP/5/ICT/2.The authors fully acknowledged Ministry of Higher Education(MOHE)and National Defence University of Malaysia for the approved fund which makes this important research viable and effective.The authors also would like to thank University Grant Commission of Bangladesh,Comilla University for the financial support.
文摘Pocket Switched Networks(PSN)represent a particular remittent network for direct communication between the handheld mobile devices.Compared to traditional networks,there is no stable topology structure for PSN where the nodes observe the mobility model of human society.It is a kind of Delay Tolerant Networks(DTNs)that gives a description to circulate information among the network nodes by the way of taking the benefit of transferring nodes from one area to another.Considering its inception,there are several schemes for message routing in the infrastructure-less environment in which human mobility is only the best manner to exchange information.For routing messages,PSN uses different techniques such asDistributed Expectation-Based Spatio-Temporal(DEBT)Epidemic(DEBTE),DEBT Cluster(DEBTC),and DEBT Tree(DEBTT).Understanding on how the network environment is affected for these routing strategies are the main motivation of this research.In this paper,we have investigated the impact of network nodes,the message copies per transmission,and the overall carrying out of these routing protocols.ONE simulator was used to analyze those techniques on the basis of delivery,overhead,and latency.The result of this task demonstrates that for a particular simulation setting,DEBTE is the best PSN routing technique among all,against DEBTC and DEBTT.
文摘Two novel improved variants of reptile search algorithm(RSA),RSA with opposition-based learning(ORSA)and hybrid ORSA with pattern search(ORSAPS),are proposed to determine the proportional,integral,and derivative(PID)controller parameters of an automatic voltage regulator(AVR)system using a novel objective function with augmented flexibility.In the proposed algorithms,the opposition-based learning technique improves the global search abilities of the original RSA algorithm,while the hybridization with the pattern search(PS)algorithm improves the local search abilities.Both algorithms are compared with the original RSA algorithm and have shown to be highly effective algorithms for tuning the PID controller parameters of an AVR system by getting superior results.Several analyses such as transient,stability,robustness,disturbance rejection,and trajectory tracking are conducted to test the performance of the proposed algorithms,which have validated the good promise of the proposed methods for controller designs.The performances of the proposed design approaches are also compared with the previously reported PID controller parameter tuning approaches to assess their success.It is shown that both proposed approaches obtain excellent and robust results among all compared ones.That is,with the adjustment of the weight factorα,which is introduced by the proposed objective function,for a system with high bandwitdh(α=1),the proposed ORSAPS-PID system has 2.08%more bandwidth than the proposed ORSA-PID system and 5.1%faster than the fastest algorithm from the literature.On the other hand,for a system where high phase and gain margins are desired(α=10),the proposed ORSA-PID system has 0.53%more phase margin and 2.18%more gain margin than the proposed ORSAPS-PID system and has 0.71%more phase margin and 2.25%more gain margin than the best performing algorithm from the literature.
文摘Wireless sensor networks(WSNs)are characterized by their ability to monitor physical or chemical phenomena in a static or dynamic location by collecting data,and transmit it in a collaborative manner to one or more processing centers wirelessly using a routing protocol.Energy dissipation is one of the most challenging issues due to the limited power supply at the sensor node.All routing protocols are large consumers of energy,as they represent the main source of energy cost through data exchange operation.Clusterbased hierarchical routing algorithms are known for their good performance in energy conservation during active data exchange in WSNs.The most common of this type of protocol is the Low-Energy Adaptive Clustering Hierarchy(LEACH),which suffers from the problem of the pseudo-random selection of cluster head resulting in large power dissipation.This critical issue can be addressed by using an optimization algorithm to improve the LEACH cluster heads selection process,thus increasing the network lifespan.This paper proposes the LEACH-CHIO,a centralized cluster-based energyaware protocol based on the Coronavirus Herd Immunity Optimizer(CHIO)algorithm.CHIO is a newly emerging human-based optimization algorithm that is expected to achieve significant improvement in the LEACH cluster heads selection process.LEACH-CHIO is implemented and its performance is verified by simulating different wireless sensor network scenarios,which consist of a variable number of nodes ranging from 20 to 100.To evaluate the algorithm performances,three evaluation indicators have been examined,namely,power consumption,number of live nodes,and number of incoming packets.The simulation results demonstrated the superiority of the proposed protocol over basic LEACH protocol for the three indicators.
文摘The development of non-linear loads at consumers has significantly impacted power supply systems.Since,the poor power quality has been found in the three-phase distribution system due to unbalanced loads,harmonic current,undesired voltage regulation,and extreme reactive power demand.To overcome this issue,Distributed STATicCOMpensator(DSTATCOM)is implemented.DSTATCOM is a shunt-connected Voltage Source Converter(VSC)that has been utilized in distribution networks to balance the bus voltage in terms of enhancing reactive power control and power factor.DSTATCOM can provide both rapid and continuous capacitive and inductive mode compensation.A rectified resistive and inductive load eliminates current harmonics in a three-phase power supply.The synchronous fundamental DQ frame is a time-domain approach developed from three-phase system space vector transformations has been designed using MATLAB/Simulink.The DQ theory is used to produce the reference signal for the Pulse Width Modulation(PWM)generator.In addition,a traditional Propor-tional Integral Derivative(PID)controller is designed and compared with pro-posed soft computing approaches such as Fuzzy–PID and Artificial Neural Network(ANN-PID)and compared accurate reference current determination for Direct Current(DC)bus through DC link.An Analytical explores the pro-posed control strategies given to establish superior outcomes.Finally,total harmo-nic distortion analysis should be taken for performance analysis of the proposed system with IEEE standards.
文摘Wireless sensor network(WSN)is a group of interconnected sensor nodes that work wirelessly to capture the information of surroundings.The routing of the network is a challenging task.The routing of WSN is classified as proactive,reactive,and hybrid.Adhoc on-demand distance vector(AODV)routing is an example of reactive routing based on the demand route formations among different nodes in the network.The research article emphasizes the design and simulation of the AODV routing hardware chip using very-high-speed integrated circuit hardware description language(VHDL)programming in Xilinx integrated synthesis environment(ISE)14.7 software.The performance of the chip is studied based on the field-programmable gate array(FPGA)hardware parameters such as slices,lookup table(LUTs),input/output block(IOB),flipflops,and memory for the different configurations of the network(N=10,20….100).The delay and frequency are also estimated on the Virtex-5 FPGA.The performance of the WSN with AODV routing is also analyzed based on the packet delivery ratio,throughput,delay,and control overhead.The simulation test cases verified the 8-bit,64-bit,and 128-bit data communication within the nodes.
文摘This paper proposes a new peak current control switching(PCCS)method for single-phase inverter in photovoltaic(PV)generation system.This method minimizes the difference between a peak current and the current command with a constant switching frequency.In this paper,the principle and the simulation results of the proposed method are described.In this paper,the principle and the simulated transient characteristics of this PCCS method are described.From the results,it is clarified that the proposed switching method is effective.
基金Faculty of Engineering&Technology,University Polytechnic,JMI,New Delhi to support this research.
文摘The challenges that electric vehicles(EVs)must overcome today include the high cost of batteries,poor specific energy,and ineffectiveness in estimating the state of batteries using traditional methods.This article reviews(i)current research trends in EV technology according to the Web of Science database,(ii)current states of battery technology in EVs,(iii)advancements in battery technology,(iv)safety concerns with high-energy batteries and their environmental impacts,(v)modern algorithms to evaluate battery state,(vi)wireless charging technology and its practical limitations,(vii)key barriers to battery technology,and(viii)conclusions and recommendations are also provided.This paper examines energy-storage technologies for EVs,including lithium-ion,solid-state,and lithium-air batteries,fuel cells,and ultracapacitors.The core characteristics,advantages,disadvantages,and safety concerns associated with these batteries are discussed.Internet-of-Things(IoT)-based approaches are described to assess the battery state in real-time.Furthermore,for enhanced electric mobility,wireless power transfer charging techniques are discussed.Finally,recent advancements and potential outcomes for future EV technologies are outlined.
基金Scientic and Technological Research Council of Turkey(TUBITAK),under grand,No:113E771.
文摘Subcutaneous vein network plays important roles to maintain microcirculation that is related to some diagnostic aspects.Despite developments of optical imaging technologies,still the difficulties about deep skin vascular imaging have been continued.On the other hand,since hemoglobin con-centration of human blood has key role in the veins imaging by optical manner,the used wavelength in vascular imaging,must be chosen considering absorption of hemoglobin.In this research,we constructed a near infrared(NIR)light source because of lower absorption of hemoglobin in this optical region.To obtain vascular image,reflectance geometry was used.Next,from recorded images,vascular network analysis,such as calculation of width of vascular of interest and complexity of selected region were implemented.By comparing with other modalities,we observed that proposed imaging system has great advantages including nonionized radiation,moderate penetration depth of 0.5-3 mm and diameter of 1 mm,cost-effective and algorit hmic simplicity for analysis.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University,Saudi Arabia,for funding this work through the Research Group Program under Grant No:RGP.2/108/42.
文摘Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost,gains,energy,mass,and so on.In order to solve optimization problems,metaheuristic algorithms are essential.Most of these techniques are influenced by collective knowledge and natural foraging.There is no such thing as the best or worst algorithm;instead,there are more effective algorithms for certain problems.Therefore,in this paper,a new improved variant of a recently proposed metaphorless Runge-Kutta Optimization(RKO)algorithm,called Improved Runge-Kutta Optimization(IRKO)algorithm,is suggested for solving optimization problems.The IRKO is formulated using the basic RKO and local escaping operator to enhance the diversification and intensification capability of the basic RKO version.The performance of the proposed IRKO algorithm is validated on 23 standard benchmark functions and three engineering constrained optimization problems.The outcomes of IRKO are compared with seven state-of-the-art algorithms,including the basic RKO algorithm.Compared to other algorithms,the recommended IRKO algorithm is superior in discovering the optimal results for all selected optimization problems.The runtime of IRKO is less than 0.5 s for most of the 23 benchmark problems and stands first for most of the selected problems,including real-world optimization problems.
基金This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2021R1A6A1A03039493).
文摘Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control,navigation,route mapping,etc.The traffic prediction model aims to predict the traffic conditions based on the past traffic data.For more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis model.This study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALSTM)model for traffic prediction.The proposed OCNN-ALSTM technique primarily preprocesses the traffic data by the use of min-max normalization technique.Besides,OCNN-ALSTM technique was executed for classifying and predicting the traffic data in real time cases.For enhancing the predictive outcomes of the OCNN-ALSTM technique,the bird swarm algorithm(BSA)is employed to it and thereby overall efficacy of the network gets improved.The design of BSA for optimal hyperparameter tuning of the CNN-ALSTM model shows the novelty of the work.The experimental validation of the OCNNALSTM technique is performed using benchmark datasets and the results are examined under several aspects.The simulation results reported the enhanced outcomes of the OCNN-ALSTM model over the recent methods under several dimensions.
文摘The design and analysis of a fuel cell vehi-cle-to-grid(FCV2G)system with a high voltage conver-sion interface is proposed.The system aims to maximize the utilization of fuel cell vehicles(FCVs)as distributed energy resources,allowing them to actively participate in the energy market.The proposed FCV2G system has FCVs,power electronics interfaces,and the electrical grid.The power electronics interfaces are responsible for con-verting the low-voltage output of the fuel cell stack into high-voltage DC power,and ensuring efficient power transfer between the FCVs and the grid.To optimize the operation of the FCV2G system,the momentum search algorithm(MSA)is employed.By applying MSA,the FCV2G system can achieve optimal power dispatch,con-sidering factors such as energy efficiency,grid stability,and economic feasibility.The proposed method is tested in MATLAB.The best MSA and dynamic load profile solu-tions are run for 24 h and the results show that 100%import of FCVs 51.0%more than 100%electric vehicle.Peak-cutting and vehicle-to-grid service revenue are 30.5%and 95.0%greater,respectively.Low discharge loss,high capacity,and high discharge power are the main advantages of FCVs.The benchmark FCVs ratio of 15%is used for sensitivity analysis.The findings reveal that the overall advantages of FCV2G are improved.Index Terms—Continuous conduction mode,DC-DC converter,discontinuous conduction mode,fuel cell vehi-cle,utility-grids,vehicle-to-grid.
基金This work was supported by the Universiti Kebangsaan Malaysia,Malaysia research grant code GUP-2019-005.
文摘This paper presents a new Double-E-Triple-H-Shaped NRI(negative refractive index)metamaterial(MM)for dual-band microwave sensing applications.Here,a horizontal H-shaped metal structure is enclosed by two face-to-face E-shaped metal structures.This double-E-H-shaped design is also encased by two vertical H-shaped structures along with some copper links.Thus,the Double-E-Triple-H-Shaped configuration is developed.Two popular substrate materials of Rogers RO 3010 and FR-4 were adopted for analyzing the characteristics of the unit cell.The proposed structure exhibits transmission resonance inside the S-band with NRI and ENG(Epsilon Negative)metamaterial properties,and inside the C-band with ENG and MNG(Mu Negative)metamaterial properties.A good effective medium ratio(EMR)of 8.06 indicates the compactness and effectiveness of the proposed design.Further analysis has been done by changing the thickness of the substrate material as well and a significant change in the effective medium ratio is found.The validity of the proposed structure is confirmed by an equivalent circuit model.The simulated result agrees well with the calculated result.For exploring microwave sensing applications of the proposed unit cell,permittivity and pressure sensitivity performance were investigated in different simulation arrangements.The compact size,effective parameters,high sensitivity and a good EMR represent the proposed metamaterial as a promising solution for S-band and C-band microwave sensing applications.
基金This work was supported by Research Support Fund(RSF)of Symbiosis International(Deemed University),Pune,India。
文摘In the era of digital signal processing,like graphics and computation systems,multiplication-accumulation is one of the prime operations.A MAC unit is a vital component of a digital system,like different Fast Fourier Transform(FFT)algorithms,convolution,image processing algorithms,etcetera.In the domain of digital signal processing,the use of normalization architecture is very vast.The main objective of using normalization is to performcomparison and shift operations.In this research paper,an evolutionary approach for designing an optimized normalization algorithm is proposed using basic logical blocks such as Multiplexer,Adder etc.The proposed normalization algorithm is further used in designing an 8×8 bit Signed Floating-Point Multiply-Accumulate(SFMAC)architecture.Since the SFMAC can accept an 8-bit significand and a 3-bit exponent,the input to the said architecture can be somewhere between−(7.96872)_(10) to+(7.96872)_(10).The proposed architecture is designed and implemented using the Cadence Virtuoso using 90 and 130 nm technologies(in Generic Process Design Kit(GPDK)and Taiwan Semiconductor Manufacturing Company(TSMC),respectively).To reduce the power consumption of the proposed normalization architecture,techniques such as“block enabling”and“clock gating”are used rigorously.According to the analysis done on Cadence,the proposed architecture uses the least amount of power compared to its current predecessors.
文摘Any nonlinear behavior of the system is analyzed by a useful way of Total Harmonic Distortion(THD)technique.Reduced THD achieves lower peak current,higher efficiency and longer equipment life span.Simulated annealing(SA)is applied due to the effectiveness of locating solutions that are close to ideal and to challenge large-scale combinatorial optimization for Permanent Magnet Synchronous Machine(PMSM).The parameters of direct torque controllers(DTC)for the drive are automatically adjusted by the optimization algorithm.Advantages of the PI-Fuzzy-SA algorithm are retained when used together.It also improves the rate of system convergence.Speed response improvement and har-monic reduction is achieved with SA-based DTC for PMSM.This mechanism is known to be faster than other algorithms.Also,it is observed that as compared to other algorithms,the projected algorithm yields a reduced total harmonic distor-tion.As a result of the employment of Space Vector Modulation(SVM)techni-que,the system is resistant to changes in motor specifications and load torque.Through MATLAB&Simulink simulation,the experiment is done and the per-formance is calculated for the controller.
