A versatile analytical method(VAM) for calculating the harmonic components of the magnetomotive force(MMF) generated by diverse armature windings in AC machines has been proposed, and the versatility of this method ha...A versatile analytical method(VAM) for calculating the harmonic components of the magnetomotive force(MMF) generated by diverse armature windings in AC machines has been proposed, and the versatility of this method has been established in early literature. However, its practical applications and significance in advancing the analysis of AC machines need further elaboration. This paper aims to complement VAM by augmenting its theory, offering additional insights into its conclusions, as well as demonstrating its utility in assessing armature windings and its application of calculating torque for permanent magnet synchronous machines(PMSM). This work contributes to advancing the analysis of AC machines and underscores the potential for improved design and performance optimization.展开更多
With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage co...With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.展开更多
The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access cont...The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.展开更多
The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information.Compared with previous work,a closed-loop optimal solution to the control p...The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information.Compared with previous work,a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first time.The main challenge lies in three aspects:Firstly,the asymmetric information results in coupling between control and estimation and failure of the separation principle.Secondly,two extra unknown variables are generated by asymmetric information(different information filtration)when solving forward-backward stochastic difference equations.Thirdly,the existence of additive noise makes the study of mean-square boundedness an obstacle.The adopted technique is proving and assuming the linear form of controllers and establishing the equivalence between the two systems with and without additive noise.A dual-motor parallel drive system is presented to demonstrate the validity of the proposed algorithm.展开更多
The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered ...The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.展开更多
In this paper,a control scheme based on current optimization is proposed for dual three-phase permanent-magnet synchronous motor(DTP-PMSM)drive to reduce the low-frequency temperature swing.The reduction of temperatur...In this paper,a control scheme based on current optimization is proposed for dual three-phase permanent-magnet synchronous motor(DTP-PMSM)drive to reduce the low-frequency temperature swing.The reduction of temperature swing can be equivalent to reducing maximum instantaneous phase copper loss in this paper.First,a two-level optimization aiming at minimizing maximum instantaneous phase copper loss at each electrical angle is proposed.Then,the optimization is transformed to a singlelevel optimization by introducing the auxiliary variable for easy solving.Considering that singleobjective optimization trades a great total copper loss for a small reduction of maximum phase copper loss,the optimization considering both instantaneous total copper loss and maximum phase copper loss is proposed,which has the same performance of temperature swing reduction but with lower total loss.In this way,the proposed control scheme can reduce maximum junction temperature by 11%.Both simulation and experimental results are presented to prove the effectiveness and superiority of the proposed control scheme for low-frequency temperature swing reduction.展开更多
In this paper, the issues of stochastic stability analysis and fault estimation are investigated for a class of continuoustime Markov jump piecewise-affine(PWA) systems against actuator and sensor faults. Firstly, a n...In this paper, the issues of stochastic stability analysis and fault estimation are investigated for a class of continuoustime Markov jump piecewise-affine(PWA) systems against actuator and sensor faults. Firstly, a novel mode-dependent PWA iterative learning observer with current feedback is designed to estimate the system states and faults, simultaneously, which contains both the previous iteration information and the current feedback mechanism. The auxiliary feedback channel optimizes the response speed of the observer, therefore the estimation error would converge to zero rapidly. Then, sufficient conditions for stochastic stability with guaranteed performance are demonstrated for the estimation error system, and the equivalence relations between the system information and the estimated information can be established via iterative accumulating representation.Finally, two illustrative examples containing a class of tunnel diode circuit systems are presented to fully demonstrate the effectiveness and superiority of the proposed iterative learning observer with current feedback.展开更多
Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental problems.Its attributes as a non-toxic,low-carbon,and economical substitute for conventio...Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental problems.Its attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation infrastructure.In this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering field.To achieve this goal,a new approach using convolutional neural networks(CNNs)has been adopted.This study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly ash.The selection of optimal input parameters is guided by two distinct criteria.The first criterion leverages insights garnered from previous research on the influence of individual features on compressive strength.The second criterion scrutinizes the impact of these features within the model’s predictive framework.Key to enhancing the CNN model’s performance is the meticulous determination of the optimal hyperparameters.Through a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s robustness.The model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score analyses.Furthermore,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction methods.To unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rate.The study culminates in compelling findings that underscore the CNN model’s accurate prediction of geopolymer concrete compressive strength.To maximize the dataset’s potential,the application of bivariate plots unveils nuanced trends and interactions among variables,fortifying the consistency with earlier research.Evidenced by promising prediction accuracy,the study’s outcomes hold significant promise in guiding the development of innovative geopolymer concrete formulations,thereby reinforcing its role as an eco-conscious and robust construction material.The findings prove that the CNN model accurately estimated geopolymer concrete’s compressive strength.The results show that the prediction accuracy is promising and can be used for the development of new geopolymer concrete mixes.The outcomes not only underscore the significance of leveraging technology for sustainable construction practices but also pave the way for innovation and efficiency in the field of civil engineering.展开更多
From the perspective of a community energy operator,a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads.The day-ahead scheduling an...From the perspective of a community energy operator,a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads.The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system(IES)before and after;the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme,taking into account the fluctuation of wind turbine output and load within a short period of time and according to the different response rates of heat and cooling power,and solves the adjusted output of each controllable device.The simulation results show that the optimal scheduling of controllable loads effectively reduces the comprehensive operating costs of community IES;the two-stage optimal scheduling model can meet the energy demand of customers while effectively and timely suppressing the random fluctuations on both sides of the source and load during the intra-day stage,realizing the economic and smooth operation of IES.展开更多
This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a suffi...This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.展开更多
ZnO-Bi2O3-based varistor ceramics doped with Yb2O3 in the range from 0 to 0.4%(molar fraction) were obtained by a solid reaction route.The X-ray diffractometry(XRD) and scanning electron microscopy(SEM) were applied t...ZnO-Bi2O3-based varistor ceramics doped with Yb2O3 in the range from 0 to 0.4%(molar fraction) were obtained by a solid reaction route.The X-ray diffractometry(XRD) and scanning electron microscopy(SEM) were applied to characterize the phases and microstructure of the varistor ceramics,and a DC parameter instrument for varistor ceramics was applied to investigate their electrical properties and V-I characteristics.The XRD analysis of the samples shows that the ZnO phase,Bi2O3 phase,Zn7Sb2O12-type spinel phase and Zn2Bi3Sb3O14-type pyrochlore are present,and the Yb2O3 phases and Sb2O4 phases are found in varistor ceramics with increasing amounts of Yb2O3.The average size of ZnO grain firstly increases and then decreases with the increase of Yb2O3 content.The result also shows that the threshold voltage is between 656 V/mm and 1 232 V/mm,the nonlinear coefficient is in the range of 14.1-22.3,and the leakage current is between 0.60 μA and 19.6 μA.The 0.20% Yb2O3-added ZnO-Bi2O3-based varistor ceramics sintered at 900 °C have the best electrical characteristics.展开更多
This article describes an Internet based laboratory (NETLAB) developed at Zhejiang University for electrical engi- neering education. A key feature of the project is the use of real experimental systems rather than si...This article describes an Internet based laboratory (NETLAB) developed at Zhejiang University for electrical engi- neering education. A key feature of the project is the use of real experimental systems rather than simulation or virtual reality. NELTAB provides remote access to a wide variety of experiments, including not only basic electrical and electronic experiments but also many innovative control experiments. Students can effectively use the laboratory at any time and from anywhere. NETLAB has been in operation since July 2003.展开更多
It is important to distribute the load efficiently to minimize the cost of the economic dispatch of electrical power system. The uncertainty and volatility of wind energy make the economic dispatch much more complex w...It is important to distribute the load efficiently to minimize the cost of the economic dispatch of electrical power system. The uncertainty and volatility of wind energy make the economic dispatch much more complex when the general power systems are combined with wind farms. The short term wind power prediction method was discussed in this paper. The method was based on the empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD). Furthermore,the effect of wind farms on the traditional economic dispatch of electrical power system was analyzed. The mathematical model of the economic dispatch was established considering the environmental factors and extra spinning reserve cost. The multi-objective co-evolutionary algorithm was used to figure out the model. And the results were compared with the NSGA-Ⅱ(non-dominated sorting genetic algorithm-Ⅱ) to verify its feasibility.展开更多
A reliable,efficient and economical power supply for dielectric barrier discharge(DBD)is essential for its industrial applications.However,the equivalent load parameters complicate the design of power supply as they a...A reliable,efficient and economical power supply for dielectric barrier discharge(DBD)is essential for its industrial applications.However,the equivalent load parameters complicate the design of power supply as they are variable and varied nonlinearly in response to varied voltage and power.In this paper the equivalent electrical parameters of DBD are predicted using a neural network,which is beneficial for the design of power supply and helps to investigate how the electrical parameters influence the equivalent load parameters.The electrical parameters including voltage and power are determined to be the inputs of the neural network model,as these two parameters greatly influence the discharge type and the equivalent DBD load parameters which are the outputs of the model.The voltage and power are decoupled with pulse density modulation(PDM)and hence the impact of the two electrical parameters is discussed individually.The neural network model is trained with the back-propagation(BP)algorithm.The obtained neural network model is evaluated by the relative error,and the prediction has a good agreement with the practical values obtained in experiments.展开更多
Thermal damage of malignant tissue is generally determined not only by the characteristics of bio-tissues and nanoparticles but also the nanofluid concentration distributions due to different injection methods during ...Thermal damage of malignant tissue is generally determined not only by the characteristics of bio-tissues and nanoparticles but also the nanofluid concentration distributions due to different injection methods during magnetic hyperthermia.The latter has more advantages in improving the therapeutic effect with respect to the former since it is a determining factor for the uniformity of nanofluid concentration distribution inside the tumor region.This study investigates the effect of bio-tissue deformation due to intratumoral injection on the thermal damage behavior and treatment temperature distribution during magnetic hyperthermia,in which both the bio-tissue deformation due to nanofluid injection and the mass diffusion after injection behavior are taken into consideration.The nanofluid flow behavior is illustrated by two different theoretical models in this study,which are Navier–Stokes equation inside syringe needle and modified Darcy’s law inside bio-tissue.The diffusion behavior after nanofluid injection is expressed by a modified convection–diffusion equation.A proposed three-dimensional liver model based on the angiographic data is set to be the research object in this study,in which all bio-tissues are assumed to be deformable porous media.Simulation results demonstrate that the injection point for syringe needle can generally achieve the maximum value in the tissue pressure,deformation degree,and interstitial flow velocity during the injection process,all of which then drop sharply with the distance away from the injection center.In addition to the bio-tissue deformation due to injection behavior,the treatment temperature is also highly relevant to determine both the diffusion duration and blood perfusion rate due to the thermal damage during the therapy.展开更多
We present the variations of electrical parameters of dielectric barrier discharge(DBD)when the DBD generator is used for the material modification,whereas the relevant physical mechanism is also elaborated.An equival...We present the variations of electrical parameters of dielectric barrier discharge(DBD)when the DBD generator is used for the material modification,whereas the relevant physical mechanism is also elaborated.An equivalent circuit model is applied for a DBD generator working in a filament discharging mode,considering the addition of epoxy resin(EP)as the plasma modified material.The electrical parameters are calculated through the circuit model.The surface conductivity,surface potential decay,trap distributions and surface charge distributions on the EP surface before and after plasma treatments were measured and calculated.It is found that the coverage area of micro-discharge channels on the EP surface is increased with the discharging time under the same applied AC voltage.The results indicate that the plasma modified material could influence the ignition of new filaments in return during the modification process.Moreover,the surface conductivity and density of shallow traps with low trap energy of the EP samples increase after the plasma treatment.The surface charge distributions indicate that the improved surface properties accelerate the movement and redistribution of charge carriers on the EP surface.The variable electrical parameters of discharge are attributed to the redistribution of deposited surface charge on the plasma modified EP sample surface.展开更多
With the continuous development and progress of science and technology in China, automation technology has occupied an important position in many fields while its application in power system is increasingly widespread...With the continuous development and progress of science and technology in China, automation technology has occupied an important position in many fields while its application in power system is increasingly widespread. Therefore, the application of electrical automation technology in power system is of great significance for power supply stability and work efficiency. In this paper, the author analyzes the application of electric automation technology in power system and makes contributions to the sustainable and stable development of power enterprises.展开更多
The nanosecond(ns) pulsed nitrogen dielectric barrier discharge(DBD) is employed to enhance the hydrophilicity of polypropylene(PP) surface and improve its application effect.The discharge characteristics of the ns pu...The nanosecond(ns) pulsed nitrogen dielectric barrier discharge(DBD) is employed to enhance the hydrophilicity of polypropylene(PP) surface and improve its application effect.The discharge characteristics of the ns pulsed nitrogen DBD with different pulse rise times(from 50to 500 ns) are investigated by electrical and optical diagnostic methods and the discharge uniformity is quantitatively analyzed by image processing method.To characterize the surface hydrophilicity,the water contact angle(WCA) is measured,and the physical morphology and chemical composition of PP before and after modification are analyzed to explore the effect of plasma on PP surface.It is found that with increasing pulse rise time from 50 to 500 ns,DBD uniformity becomes worse,energy efficiency decreases from 20% to 10.8%,and electron density decrease from 6.6 × 10^(11)to 5.5 × 10^(11)cm^(-3).The tendency of electron temperature is characterized with the intensity ratio of N_(2)/N_(2)^(+)emission spectrum,which decreases from 17.4 to15.9 indicating the decreasing of T_(e) with increasing pulse rise time from 50 to 500 ns.The PP surface treated with 50 ns pulse rise time DBD has a lower WCA(~47°),while the WCA of PP treated with 100 to 500 ns pulse rise time DBD expands gradually(~50°–57°).According to the study of the fixed-point WCA values,the DBD-treated PP surface has superior uniformity under50 ns pulse rise time(3° variation) than under 300 ns pulse rise time(8° variation).After DBD treatment,the increased surface roughness from 2.0 to 9.8 nm and hydrophilic oxygencontaining groups on the surface,i.e.hydroxyl(-OH) and carbonyl(C=O) have played the significant role to improve the sample’s surface hydrophilicity.The short pulse voltage rise time enhances the reduced electric field strength(E/n) in the discharge space and improves the discharge uniformity,which makes relatively sufficient physical and chemical reactions have taken place on the PP surface,resulting in better treatment uniformity.展开更多
An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency...An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency of laser interference fringes of an absolute gravimeter gradually increases with the fall time. Data are sparse in the early stage and dense in the late stage. The fitting accuracy of gravitational acceleration will be affected by least-squares fitting according to the fixed number of zero-crossing groups. In response to this problem, a method based on Fourier series fitting is proposed in this paper to calculate the zero-crossing point. The whole falling process is divided into five frequency bands using the Hilbert transformation. The multiplicative auto-regressive moving average model is then trained according to the number of optimal zero-crossing groups obtained by the honey badger algorithm. Through this model, the number of optimal zero-crossing groups determined in each segment is predicted by the least-squares fitting. The mean value of gravitational acceleration in each segment is then obtained. The method can improve the accuracy of gravitational measurement by more than 25% compared to the fixed zero-crossing groups method. It provides a new way to improve the measuring accuracy of an absolute gravimeter.展开更多
In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in ord...In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.展开更多
基金supported by the Natural Science Foundation of China under Grant U22A20214 and Grant 51837010。
文摘A versatile analytical method(VAM) for calculating the harmonic components of the magnetomotive force(MMF) generated by diverse armature windings in AC machines has been proposed, and the versatility of this method has been established in early literature. However, its practical applications and significance in advancing the analysis of AC machines need further elaboration. This paper aims to complement VAM by augmenting its theory, offering additional insights into its conclusions, as well as demonstrating its utility in assessing armature windings and its application of calculating torque for permanent magnet synchronous machines(PMSM). This work contributes to advancing the analysis of AC machines and underscores the potential for improved design and performance optimization.
基金supported by Science and Technology Project of SGCC(SGSW0000FZGHBJS2200070)。
文摘With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.
文摘The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.
基金supported by the National Natural Science Foundation of China(62273213,62073199,62103241)Natural Science Foundation of Shandong Province for Innovation and Development Joint Funds(ZR2022LZH001)+4 种基金Natural Science Foundation of Shandong Province(ZR2020MF095,ZR2021QF107)Taishan Scholarship Construction Engineeringthe Original Exploratory Program Project of National Natural Science Foundation of China(62250056)Major Basic Research of Natural Science Foundation of Shandong Province(ZR2021ZD14)High-level Talent Team Project of Qingdao West Coast New Area(RCTD-JC-2019-05)。
文摘The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information.Compared with previous work,a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first time.The main challenge lies in three aspects:Firstly,the asymmetric information results in coupling between control and estimation and failure of the separation principle.Secondly,two extra unknown variables are generated by asymmetric information(different information filtration)when solving forward-backward stochastic difference equations.Thirdly,the existence of additive noise makes the study of mean-square boundedness an obstacle.The adopted technique is proving and assuming the linear form of controllers and establishing the equivalence between the two systems with and without additive noise.A dual-motor parallel drive system is presented to demonstrate the validity of the proposed algorithm.
基金supported in part by the National Natural Science Foundation of China (62233012,62273087)the Research Fund for the Taishan Scholar Project of Shandong Province of Chinathe Shanghai Pujiang Program of China (22PJ1400400)。
文摘The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.
基金supported by the National Natural Science Foundation of China(No.62271109)。
文摘In this paper,a control scheme based on current optimization is proposed for dual three-phase permanent-magnet synchronous motor(DTP-PMSM)drive to reduce the low-frequency temperature swing.The reduction of temperature swing can be equivalent to reducing maximum instantaneous phase copper loss in this paper.First,a two-level optimization aiming at minimizing maximum instantaneous phase copper loss at each electrical angle is proposed.Then,the optimization is transformed to a singlelevel optimization by introducing the auxiliary variable for easy solving.Considering that singleobjective optimization trades a great total copper loss for a small reduction of maximum phase copper loss,the optimization considering both instantaneous total copper loss and maximum phase copper loss is proposed,which has the same performance of temperature swing reduction but with lower total loss.In this way,the proposed control scheme can reduce maximum junction temperature by 11%.Both simulation and experimental results are presented to prove the effectiveness and superiority of the proposed control scheme for low-frequency temperature swing reduction.
基金supported in part by the National Natural Science Foundation of China (62222310, U1813201, 61973131, 62033008)the Research Fund for the Taishan Scholar Project of Shandong Province of China+2 种基金the NSFSD(ZR2022ZD34)Japan Society for the Promotion of Science (21K04129)Fujian Outstanding Youth Science Fund (2020J06022)。
文摘In this paper, the issues of stochastic stability analysis and fault estimation are investigated for a class of continuoustime Markov jump piecewise-affine(PWA) systems against actuator and sensor faults. Firstly, a novel mode-dependent PWA iterative learning observer with current feedback is designed to estimate the system states and faults, simultaneously, which contains both the previous iteration information and the current feedback mechanism. The auxiliary feedback channel optimizes the response speed of the observer, therefore the estimation error would converge to zero rapidly. Then, sufficient conditions for stochastic stability with guaranteed performance are demonstrated for the estimation error system, and the equivalence relations between the system information and the estimated information can be established via iterative accumulating representation.Finally, two illustrative examples containing a class of tunnel diode circuit systems are presented to fully demonstrate the effectiveness and superiority of the proposed iterative learning observer with current feedback.
基金funded by the Researchers Supporting Program at King Saud University(RSPD2023R809).
文摘Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental problems.Its attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation infrastructure.In this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering field.To achieve this goal,a new approach using convolutional neural networks(CNNs)has been adopted.This study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly ash.The selection of optimal input parameters is guided by two distinct criteria.The first criterion leverages insights garnered from previous research on the influence of individual features on compressive strength.The second criterion scrutinizes the impact of these features within the model’s predictive framework.Key to enhancing the CNN model’s performance is the meticulous determination of the optimal hyperparameters.Through a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s robustness.The model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score analyses.Furthermore,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction methods.To unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rate.The study culminates in compelling findings that underscore the CNN model’s accurate prediction of geopolymer concrete compressive strength.To maximize the dataset’s potential,the application of bivariate plots unveils nuanced trends and interactions among variables,fortifying the consistency with earlier research.Evidenced by promising prediction accuracy,the study’s outcomes hold significant promise in guiding the development of innovative geopolymer concrete formulations,thereby reinforcing its role as an eco-conscious and robust construction material.The findings prove that the CNN model accurately estimated geopolymer concrete’s compressive strength.The results show that the prediction accuracy is promising and can be used for the development of new geopolymer concrete mixes.The outcomes not only underscore the significance of leveraging technology for sustainable construction practices but also pave the way for innovation and efficiency in the field of civil engineering.
基金supported in part by the National Natural Science Foundation of China(51977127)Shanghai Municipal Science and Technology Commission(19020500800)“Shuguang Program”(20SG52)Shanghai Education Development Foundation and Shanghai Municipal Education Commission.
文摘From the perspective of a community energy operator,a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads.The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system(IES)before and after;the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme,taking into account the fluctuation of wind turbine output and load within a short period of time and according to the different response rates of heat and cooling power,and solves the adjusted output of each controllable device.The simulation results show that the optimal scheduling of controllable loads effectively reduces the comprehensive operating costs of community IES;the two-stage optimal scheduling model can meet the energy demand of customers while effectively and timely suppressing the random fluctuations on both sides of the source and load during the intra-day stage,realizing the economic and smooth operation of IES.
基金supported by the National Natural Science Foundation of China under Grants 61821004,62250056,62350710214,U23A20325,62350055the Natural Science Foundation of Shandong Province,China(ZR2021ZD14,ZR2021JQ24)+2 种基金High-level Talent Team Project of Qingdao West Coast New Area,China(RCTD-JC-2019-05)Key Research and Development Program of Shandong Province,China(2020CXGC01208)Science and Technology Project of Qingdao West Coast New Area,China(2019-32,2020-20,2020-1-4).
文摘This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.
基金Project(BK2011243) supported by the Natural Science Foundation of Jiangsu Province,ChinaProject(2007DA10512711408) supported by the Visiting Scholarship of State Key Laboratory of Power Transmission Equipment & System Security and New Technology (Chongqing University),China+4 种基金Project(EIPE11204) supported by the State Key Laboratory of Electrical Insulation and Power Equipment,ChinaProject(KF201104) supported by the State Key Laboratory of New Ceramic and Fine Processing,ChinaProject(KFJJ201105) supported by the Opening Project of State Key Laboratory of Electronic Thin Films and Integrated Devices,ChinaProject(10KJD430002) supported by the Universities Natural Science Research Project of Jiangsu Province,ChinaProject(11JDG084) supported by the Research Foundation of Jiangsu University,China
文摘ZnO-Bi2O3-based varistor ceramics doped with Yb2O3 in the range from 0 to 0.4%(molar fraction) were obtained by a solid reaction route.The X-ray diffractometry(XRD) and scanning electron microscopy(SEM) were applied to characterize the phases and microstructure of the varistor ceramics,and a DC parameter instrument for varistor ceramics was applied to investigate their electrical properties and V-I characteristics.The XRD analysis of the samples shows that the ZnO phase,Bi2O3 phase,Zn7Sb2O12-type spinel phase and Zn2Bi3Sb3O14-type pyrochlore are present,and the Yb2O3 phases and Sb2O4 phases are found in varistor ceramics with increasing amounts of Yb2O3.The average size of ZnO grain firstly increases and then decreases with the increase of Yb2O3 content.The result also shows that the threshold voltage is between 656 V/mm and 1 232 V/mm,the nonlinear coefficient is in the range of 14.1-22.3,and the leakage current is between 0.60 μA and 19.6 μA.The 0.20% Yb2O3-added ZnO-Bi2O3-based varistor ceramics sintered at 900 °C have the best electrical characteristics.
基金Project supported by the Promising Project Foundation of Zheji-ang University, China
文摘This article describes an Internet based laboratory (NETLAB) developed at Zhejiang University for electrical engi- neering education. A key feature of the project is the use of real experimental systems rather than simulation or virtual reality. NELTAB provides remote access to a wide variety of experiments, including not only basic electrical and electronic experiments but also many innovative control experiments. Students can effectively use the laboratory at any time and from anywhere. NETLAB has been in operation since July 2003.
基金Innovation Program of Shanghai Municipal Education Commission,China(No.13YZ139)Climbing Peak Discipline Project of Shanghai Dianji University,China(No.15DFXK01)
文摘It is important to distribute the load efficiently to minimize the cost of the economic dispatch of electrical power system. The uncertainty and volatility of wind energy make the economic dispatch much more complex when the general power systems are combined with wind farms. The short term wind power prediction method was discussed in this paper. The method was based on the empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD). Furthermore,the effect of wind farms on the traditional economic dispatch of electrical power system was analyzed. The mathematical model of the economic dispatch was established considering the environmental factors and extra spinning reserve cost. The multi-objective co-evolutionary algorithm was used to figure out the model. And the results were compared with the NSGA-Ⅱ(non-dominated sorting genetic algorithm-Ⅱ) to verify its feasibility.
基金supported by National Natural Science Foundation of China(Nos.51107115,11347125,51407156)China Postdoctoral Science Foundation(Nos.20110491766,2014M551735)
文摘A reliable,efficient and economical power supply for dielectric barrier discharge(DBD)is essential for its industrial applications.However,the equivalent load parameters complicate the design of power supply as they are variable and varied nonlinearly in response to varied voltage and power.In this paper the equivalent electrical parameters of DBD are predicted using a neural network,which is beneficial for the design of power supply and helps to investigate how the electrical parameters influence the equivalent load parameters.The electrical parameters including voltage and power are determined to be the inputs of the neural network model,as these two parameters greatly influence the discharge type and the equivalent DBD load parameters which are the outputs of the model.The voltage and power are decoupled with pulse density modulation(PDM)and hence the impact of the two electrical parameters is discussed individually.The neural network model is trained with the back-propagation(BP)algorithm.The obtained neural network model is evaluated by the relative error,and the prediction has a good agreement with the practical values obtained in experiments.
基金Project supported by the National Natural Science Foundation of China (Grant No. 62071124)the Natural Science Foundation of Fujian Province,China (Grant No. 2020J01464)+1 种基金the Education Department of Fujian Province,China (Grant No. JAT190013)the Conselho Nacional de Desenvolvimento Cientificoe Tecnoloico (BR)(CNPq)(Grant No. 309244/2018-8)
文摘Thermal damage of malignant tissue is generally determined not only by the characteristics of bio-tissues and nanoparticles but also the nanofluid concentration distributions due to different injection methods during magnetic hyperthermia.The latter has more advantages in improving the therapeutic effect with respect to the former since it is a determining factor for the uniformity of nanofluid concentration distribution inside the tumor region.This study investigates the effect of bio-tissue deformation due to intratumoral injection on the thermal damage behavior and treatment temperature distribution during magnetic hyperthermia,in which both the bio-tissue deformation due to nanofluid injection and the mass diffusion after injection behavior are taken into consideration.The nanofluid flow behavior is illustrated by two different theoretical models in this study,which are Navier–Stokes equation inside syringe needle and modified Darcy’s law inside bio-tissue.The diffusion behavior after nanofluid injection is expressed by a modified convection–diffusion equation.A proposed three-dimensional liver model based on the angiographic data is set to be the research object in this study,in which all bio-tissues are assumed to be deformable porous media.Simulation results demonstrate that the injection point for syringe needle can generally achieve the maximum value in the tissue pressure,deformation degree,and interstitial flow velocity during the injection process,all of which then drop sharply with the distance away from the injection center.In addition to the bio-tissue deformation due to injection behavior,the treatment temperature is also highly relevant to determine both the diffusion duration and blood perfusion rate due to the thermal damage during the therapy.
基金Project supported by the National Key R&D Program of China(Grant No.2018YFB0904400)the National Natural Science Foundation of China(Grant No.51977187)+3 种基金the“Science and Technology Innovation 2025”Key Project of Ningbo City,China(Grant No.2018B10019)the Natural Science Foundation of Zhejiang Province,China(Grant No.LY18E070003)the State Key Laboratory of HVDC,Electric Power Research Institute,China Southern Power Grid(Grant No.SKLHVDC-2019-KF-18)the Fundamental Research Funds for the Central Universities,China(Grant No.2018QNA4017).
文摘We present the variations of electrical parameters of dielectric barrier discharge(DBD)when the DBD generator is used for the material modification,whereas the relevant physical mechanism is also elaborated.An equivalent circuit model is applied for a DBD generator working in a filament discharging mode,considering the addition of epoxy resin(EP)as the plasma modified material.The electrical parameters are calculated through the circuit model.The surface conductivity,surface potential decay,trap distributions and surface charge distributions on the EP surface before and after plasma treatments were measured and calculated.It is found that the coverage area of micro-discharge channels on the EP surface is increased with the discharging time under the same applied AC voltage.The results indicate that the plasma modified material could influence the ignition of new filaments in return during the modification process.Moreover,the surface conductivity and density of shallow traps with low trap energy of the EP samples increase after the plasma treatment.The surface charge distributions indicate that the improved surface properties accelerate the movement and redistribution of charge carriers on the EP surface.The variable electrical parameters of discharge are attributed to the redistribution of deposited surface charge on the plasma modified EP sample surface.
文摘With the continuous development and progress of science and technology in China, automation technology has occupied an important position in many fields while its application in power system is increasingly widespread. Therefore, the application of electrical automation technology in power system is of great significance for power supply stability and work efficiency. In this paper, the author analyzes the application of electric automation technology in power system and makes contributions to the sustainable and stable development of power enterprises.
基金supported by National Natural Science Foundation of China (Nos. 52037004, 51777091 and52250410350)Postgraduate Research&Practice Innovation Program of Jiangsu Province (No.KYCX22_1314)。
文摘The nanosecond(ns) pulsed nitrogen dielectric barrier discharge(DBD) is employed to enhance the hydrophilicity of polypropylene(PP) surface and improve its application effect.The discharge characteristics of the ns pulsed nitrogen DBD with different pulse rise times(from 50to 500 ns) are investigated by electrical and optical diagnostic methods and the discharge uniformity is quantitatively analyzed by image processing method.To characterize the surface hydrophilicity,the water contact angle(WCA) is measured,and the physical morphology and chemical composition of PP before and after modification are analyzed to explore the effect of plasma on PP surface.It is found that with increasing pulse rise time from 50 to 500 ns,DBD uniformity becomes worse,energy efficiency decreases from 20% to 10.8%,and electron density decrease from 6.6 × 10^(11)to 5.5 × 10^(11)cm^(-3).The tendency of electron temperature is characterized with the intensity ratio of N_(2)/N_(2)^(+)emission spectrum,which decreases from 17.4 to15.9 indicating the decreasing of T_(e) with increasing pulse rise time from 50 to 500 ns.The PP surface treated with 50 ns pulse rise time DBD has a lower WCA(~47°),while the WCA of PP treated with 100 to 500 ns pulse rise time DBD expands gradually(~50°–57°).According to the study of the fixed-point WCA values,the DBD-treated PP surface has superior uniformity under50 ns pulse rise time(3° variation) than under 300 ns pulse rise time(8° variation).After DBD treatment,the increased surface roughness from 2.0 to 9.8 nm and hydrophilic oxygencontaining groups on the surface,i.e.hydroxyl(-OH) and carbonyl(C=O) have played the significant role to improve the sample’s surface hydrophilicity.The short pulse voltage rise time enhances the reduced electric field strength(E/n) in the discharge space and improves the discharge uniformity,which makes relatively sufficient physical and chemical reactions have taken place on the PP surface,resulting in better treatment uniformity.
基金Project supported by the National Key R&D Program of China (Grant No. 2022YFF0607504)。
文摘An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency of laser interference fringes of an absolute gravimeter gradually increases with the fall time. Data are sparse in the early stage and dense in the late stage. The fitting accuracy of gravitational acceleration will be affected by least-squares fitting according to the fixed number of zero-crossing groups. In response to this problem, a method based on Fourier series fitting is proposed in this paper to calculate the zero-crossing point. The whole falling process is divided into five frequency bands using the Hilbert transformation. The multiplicative auto-regressive moving average model is then trained according to the number of optimal zero-crossing groups obtained by the honey badger algorithm. Through this model, the number of optimal zero-crossing groups determined in each segment is predicted by the least-squares fitting. The mean value of gravitational acceleration in each segment is then obtained. The method can improve the accuracy of gravitational measurement by more than 25% compared to the fixed zero-crossing groups method. It provides a new way to improve the measuring accuracy of an absolute gravimeter.
基金supported by the Science and Technology Project of State Grid Zhejiang Electric Power Co.,Ltd.under Grant B311JY21000A。
文摘In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.
