For a class of non-uniform output sampling hybrid system with actuator faults and bounded disturbances,an iterative learning fault diagnosis algorithm is proposed.Firstly,in order to measure the impact of fault on sys...For a class of non-uniform output sampling hybrid system with actuator faults and bounded disturbances,an iterative learning fault diagnosis algorithm is proposed.Firstly,in order to measure the impact of fault on system between every consecutive output sampling instants,the actual fault function is transformed to obtain an equivalent fault model by using the integral mean value theorem,then the non-uniform sampling hybrid system is converted to continuous systems with timevarying delay based on the output delay method.Afterwards,an observer-based fault diagnosis filter with virtual fault is designed to estimate the equivalent fault,and the iterative learning regulation algorithm is chosen to update the virtual fault repeatedly to make it approximate the actual equivalent fault after some iterative learning trials,so the algorithm can detect and estimate the system faults adaptively.Simulation results of an electro-mechanical control system model with different types of faults illustrate the feasibility and effectiveness of this algorithm.展开更多
The Bayesian sampling plans for exponential distributions are studied based on type-Ⅱ hybrid censored samples. The optimal Bayesian sampling plan is derived under a general loss function which includes the sampling c...The Bayesian sampling plans for exponential distributions are studied based on type-Ⅱ hybrid censored samples. The optimal Bayesian sampling plan is derived under a general loss function which includes the sampling cost, time-consuming cost, salvage value,and decision loss. It is employed to determine the Bayes risk and the corresponding optimal sampling plan. An explicit expression of the Bayes risk is derived. Furthermore,for the conjugate prior distribution,the closed-form formula of the Bayes decision rule can be obtained under either the linear or quadratic decision loss.展开更多
Value at Risk (VaR) is an important tool for estimating the risk of a financial portfolio under significant loss. Although Monte Carlo simulation is a powerful tool for estimating VaR, it is quite inefficient since th...Value at Risk (VaR) is an important tool for estimating the risk of a financial portfolio under significant loss. Although Monte Carlo simulation is a powerful tool for estimating VaR, it is quite inefficient since the event of significant loss is usually rare. Previous studies suggest that the performance of the Monte Carlo simulation can be improved by impor-tance sampling if the market returns follow the normality or the distributions. The first contribution of our paper is to extend the importance sampling method for dealing with jump-diffusion market returns, which can more precisely model the phenomenon of high peaks, heavy tails, and jumps of market returns mentioned in numerous empirical study papers. This paper also points out that for portfolios of which the huge loss is triggered by significantly distinct events, naively applying importance sampling method can result in poor performance. The second contribution of our paper is to develop the hybrid importance sampling method for the aforementioned problem. Our method decomposes a Monte Carlo simulation into sub simulations, and each sub simulation focuses only on one huge loss event. Thus the perform-ance for each sub simulation is improved by importance sampling method, and overall performance is optimized by determining the allotment of samples to each sub simulation by Lagrange’s multiplier. Numerical experiments are given to verify the superiority of our method.展开更多
In this paper, a decentralized proportional-derivative (PD) controller design for non-uniform motion of a Hamiltonian hybrid system is considered. A Hamiltonian hybrid system with the capability of producing a non-u...In this paper, a decentralized proportional-derivative (PD) controller design for non-uniform motion of a Hamiltonian hybrid system is considered. A Hamiltonian hybrid system with the capability of producing a non-uniform motion is developed. The structural properties of the system are investigated by means of the theory of Hamiltonian systems. A relationship between the parameters of the system and the parameters of the proposed decentralized PD controller is shown to ensure local stability and tracking performance. Simulation results are included to show the obtained non-uniform motion.展开更多
In this paper, a fast algorithm to reconstruct the spectrum of non-uniformly sampled signals is proposed. Compared with the original algorithm, the fast algorithm has a higher computational efficiency, especially when...In this paper, a fast algorithm to reconstruct the spectrum of non-uniformly sampled signals is proposed. Compared with the original algorithm, the fast algorithm has a higher computational efficiency, especially when sampling sequence is long. Particularly, a transformation matrix is built, and the reconstructed spectrum is perfectly synthesized from the spectrum of every sampling channel. The fast algorithm has solved efficiency issues of spectrum reconstruction algorithm, and making it possible for the actual application of spectrum reconstruction algorithm in multi-channel Synthetic Aperture Radar (SAR).展开更多
This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the developmen...This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where models play a core role: model-assisted, model-based, and hybrid estimation. The first two are well known, whereas the third has only recently been introduced in forest surveys. Hybrid inference mixes design- based and model-based inference, since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data.We review studies on large-area forest surveys based on model-assisted, model- based, and hybrid estimation, and discuss advantages and disadvantages of the approaches. We conclude that no general recommendations can be made about whether model-assisted, model-based, or hybrid estimation should be preferred. The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data. We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass, which are adequately related to commonly available remotely sensed data, and thus purely field based surveys remain important for several important forest parameters.展开更多
In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method (HH...In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method (HHTME), which combines the testabi- lity structure model (TSM) with the testability Bayesian networks model (TBNM), is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model (HHTM) is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.展开更多
The convective heat transfer of hybrid nanoliquids within a concentric annulus has wide engineering applications such as chemical industries, solar collectors, gas turbines, heat exchangers, nuclear reactors, and elec...The convective heat transfer of hybrid nanoliquids within a concentric annulus has wide engineering applications such as chemical industries, solar collectors, gas turbines, heat exchangers, nuclear reactors, and electronic component cooling due to their high heat transport rate. Hence, in this study, the characteristics of the heat transport mechanism in an annulus filled with the Ag-MgO/H_2O hybrid nanoliquid under the influence of quadratic thermal radiation and quadratic convection are analyzed. The nonuniform heat source/sink and induced magnetic field mechanisms are used to govern the basic equations concerning the transport of the composite nanoliquid. The dependency of the Nusselt number on the effective parameters(thermal radiation, nonlinear convection,and temperature-dependent heat source/sink parameter) is examined through sensitivity analyses based on the response surface methodology(RSM) and the face-centered central composite design(CCD). The heat transport of the composite nanoliquid for the spacerelated heat source/sink is observed to be higher than that for the temperature-related heat source/sink. The mechanisms of quadratic convection and quadratic thermal radiation are favorable for the momentum of the nanoliquid. The heat transport rate is more sensitive towards quadratic thermal radiation.展开更多
To study the heating mechanism of electron cyclotron resonance thruster(ECRT)immersed in a non-uniform magnetic field,experiments and simulations are performed based on an electron cyclotron resonance plasma source at...To study the heating mechanism of electron cyclotron resonance thruster(ECRT)immersed in a non-uniform magnetic field,experiments and simulations are performed based on an electron cyclotron resonance plasma source at ASIPP.It is found that the first harmonic of electron cyclotron resonance is essential for plasma ignition at high magnetic field(0.0875 T),while the plasma can sustain without the first and second harmonics of electron cyclotron resonance at low magnetic field(till 0.0170 T).Evidence of radial hollow density profile indicates that upper hybrid resonance,which has strong edge heating effect,is the heating mechanism of low-field ECRT.The heating mode transition from electron cyclotron resonance to upper hybrid resonance is also revealed.Interestingly,the evolutions of electron temperature and electron density with input power experience a‘delayed’jump,which may be correlated with the different power levels required for cyclotron and ionization.Moreover,when the field strength decreased,the variation of electron density behaves in an opposite trend with that of electron temperature,implying a possible competition of power deposition between them.The present work is of great interest for understanding the plasma discharge in ECRT especially immersed in a non-uniform magnetic field,and designing efficient ECRT using low magnetic field for economic space applications.展开更多
Flying plots detection has been the focus of relay protection in power system for a long time. With the promotion of Smart substation in our country, the number of SV devices is greatly increased. Abnormal data (flyin...Flying plots detection has been the focus of relay protection in power system for a long time. With the promotion of Smart substation in our country, the number of SV devices is greatly increased. Abnormal data (flying plot) caused by sampling device itself has brought tremendous pressure to the power system. The traditional flying plot detection algorithm has plenty of defects, such as low pertinence, low sensitivity and long sampling period. This paper proposes a new algorithm to identify flying plot by analyzing the wave form characteristics of sampling data. The traditional waveform recognition methods are combined in this algorithm. It has the concept of standard wave window and can distinguish flying plot in a short time. In addition, sine recovery algorithm is used to recover the flying plot. This paper uses PSCAD software to verify the validity of this algorithm. Simulation results show that the proposed method has high reliability.展开更多
并网运行的交直流混合微网中,交流侧接入非线性负载会导致公共并网点(point of common coupling,PCC)处电流出现明显畸变。为避免引入额外有源滤波器装置,在基于综合惯量的互联变换器控制基础上,叠加准比例谐振控制器用于谐波补偿控制,...并网运行的交直流混合微网中,交流侧接入非线性负载会导致公共并网点(point of common coupling,PCC)处电流出现明显畸变。为避免引入额外有源滤波器装置,在基于综合惯量的互联变换器控制基础上,叠加准比例谐振控制器用于谐波补偿控制,通过公共并网点处电流反馈信号,实现电流正弦性和交直流侧功率平衡。同时,在谐波补偿环节引入多采率控制,解决了互联变换器低开关频率控制过程中的延时而导致的谐波重构误差问题,改善谐波补偿效果,并给出准比例谐振控制器参数的设计过程。基于Matlab/Sinmulink仿真实验结果表明所提方案稳态特性好,动态响应快,对负荷突变适应性好,控制算法简单可靠。展开更多
基金supported by the National Natural Science Foundation of China(61273070,61203092)the Enterprise-college-institute Cooperative Project of Jiangsu Province(BY2015019-21)+1 种基金111 Project(B12018)the Fun-damental Research Funds for the Central Universities(JUSRP51733B)
文摘For a class of non-uniform output sampling hybrid system with actuator faults and bounded disturbances,an iterative learning fault diagnosis algorithm is proposed.Firstly,in order to measure the impact of fault on system between every consecutive output sampling instants,the actual fault function is transformed to obtain an equivalent fault model by using the integral mean value theorem,then the non-uniform sampling hybrid system is converted to continuous systems with timevarying delay based on the output delay method.Afterwards,an observer-based fault diagnosis filter with virtual fault is designed to estimate the equivalent fault,and the iterative learning regulation algorithm is chosen to update the virtual fault repeatedly to make it approximate the actual equivalent fault after some iterative learning trials,so the algorithm can detect and estimate the system faults adaptively.Simulation results of an electro-mechanical control system model with different types of faults illustrate the feasibility and effectiveness of this algorithm.
基金Natural Science Foundation of Guangdong Province of China(No.2016A030307019)the Higher Education Colleges and Universities Innovation Strong School Project of Guangdong Province,China(No.2016KTSCX153)
文摘The Bayesian sampling plans for exponential distributions are studied based on type-Ⅱ hybrid censored samples. The optimal Bayesian sampling plan is derived under a general loss function which includes the sampling cost, time-consuming cost, salvage value,and decision loss. It is employed to determine the Bayes risk and the corresponding optimal sampling plan. An explicit expression of the Bayes risk is derived. Furthermore,for the conjugate prior distribution,the closed-form formula of the Bayes decision rule can be obtained under either the linear or quadratic decision loss.
文摘Value at Risk (VaR) is an important tool for estimating the risk of a financial portfolio under significant loss. Although Monte Carlo simulation is a powerful tool for estimating VaR, it is quite inefficient since the event of significant loss is usually rare. Previous studies suggest that the performance of the Monte Carlo simulation can be improved by impor-tance sampling if the market returns follow the normality or the distributions. The first contribution of our paper is to extend the importance sampling method for dealing with jump-diffusion market returns, which can more precisely model the phenomenon of high peaks, heavy tails, and jumps of market returns mentioned in numerous empirical study papers. This paper also points out that for portfolios of which the huge loss is triggered by significantly distinct events, naively applying importance sampling method can result in poor performance. The second contribution of our paper is to develop the hybrid importance sampling method for the aforementioned problem. Our method decomposes a Monte Carlo simulation into sub simulations, and each sub simulation focuses only on one huge loss event. Thus the perform-ance for each sub simulation is improved by importance sampling method, and overall performance is optimized by determining the allotment of samples to each sub simulation by Lagrange’s multiplier. Numerical experiments are given to verify the superiority of our method.
文摘In this paper, a decentralized proportional-derivative (PD) controller design for non-uniform motion of a Hamiltonian hybrid system is considered. A Hamiltonian hybrid system with the capability of producing a non-uniform motion is developed. The structural properties of the system are investigated by means of the theory of Hamiltonian systems. A relationship between the parameters of the system and the parameters of the proposed decentralized PD controller is shown to ensure local stability and tracking performance. Simulation results are included to show the obtained non-uniform motion.
文摘In this paper, a fast algorithm to reconstruct the spectrum of non-uniformly sampled signals is proposed. Compared with the original algorithm, the fast algorithm has a higher computational efficiency, especially when sampling sequence is long. Particularly, a transformation matrix is built, and the reconstructed spectrum is perfectly synthesized from the spectrum of every sampling channel. The fast algorithm has solved efficiency issues of spectrum reconstruction algorithm, and making it possible for the actual application of spectrum reconstruction algorithm in multi-channel Synthetic Aperture Radar (SAR).
文摘This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where models play a core role: model-assisted, model-based, and hybrid estimation. The first two are well known, whereas the third has only recently been introduced in forest surveys. Hybrid inference mixes design- based and model-based inference, since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data.We review studies on large-area forest surveys based on model-assisted, model- based, and hybrid estimation, and discuss advantages and disadvantages of the approaches. We conclude that no general recommendations can be made about whether model-assisted, model-based, or hybrid estimation should be preferred. The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data. We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass, which are adequately related to commonly available remotely sensed data, and thus purely field based surveys remain important for several important forest parameters.
基金supported by the National Defense Pre-research Foundation of China(51327030104)
文摘In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method (HHTME), which combines the testabi- lity structure model (TSM) with the testability Bayesian networks model (TBNM), is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model (HHTM) is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.
文摘The convective heat transfer of hybrid nanoliquids within a concentric annulus has wide engineering applications such as chemical industries, solar collectors, gas turbines, heat exchangers, nuclear reactors, and electronic component cooling due to their high heat transport rate. Hence, in this study, the characteristics of the heat transport mechanism in an annulus filled with the Ag-MgO/H_2O hybrid nanoliquid under the influence of quadratic thermal radiation and quadratic convection are analyzed. The nonuniform heat source/sink and induced magnetic field mechanisms are used to govern the basic equations concerning the transport of the composite nanoliquid. The dependency of the Nusselt number on the effective parameters(thermal radiation, nonlinear convection,and temperature-dependent heat source/sink parameter) is examined through sensitivity analyses based on the response surface methodology(RSM) and the face-centered central composite design(CCD). The heat transport of the composite nanoliquid for the spacerelated heat source/sink is observed to be higher than that for the temperature-related heat source/sink. The mechanisms of quadratic convection and quadratic thermal radiation are favorable for the momentum of the nanoliquid. The heat transport rate is more sensitive towards quadratic thermal radiation.
基金Chinese Academy of Sciences‘100 Talent’Program(B),Pre-research of Key Laboratory Fund for Equipment(No.61422070306)Shanghai Engineering Research Center of Space Engine(No.17DZ2280800)+1 种基金National Postdoctoral Program for Innovative Talents(No.BX201700248)China Postdoctoral Science Foundation(No.2017M622035)。
文摘To study the heating mechanism of electron cyclotron resonance thruster(ECRT)immersed in a non-uniform magnetic field,experiments and simulations are performed based on an electron cyclotron resonance plasma source at ASIPP.It is found that the first harmonic of electron cyclotron resonance is essential for plasma ignition at high magnetic field(0.0875 T),while the plasma can sustain without the first and second harmonics of electron cyclotron resonance at low magnetic field(till 0.0170 T).Evidence of radial hollow density profile indicates that upper hybrid resonance,which has strong edge heating effect,is the heating mechanism of low-field ECRT.The heating mode transition from electron cyclotron resonance to upper hybrid resonance is also revealed.Interestingly,the evolutions of electron temperature and electron density with input power experience a‘delayed’jump,which may be correlated with the different power levels required for cyclotron and ionization.Moreover,when the field strength decreased,the variation of electron density behaves in an opposite trend with that of electron temperature,implying a possible competition of power deposition between them.The present work is of great interest for understanding the plasma discharge in ECRT especially immersed in a non-uniform magnetic field,and designing efficient ECRT using low magnetic field for economic space applications.
文摘Flying plots detection has been the focus of relay protection in power system for a long time. With the promotion of Smart substation in our country, the number of SV devices is greatly increased. Abnormal data (flying plot) caused by sampling device itself has brought tremendous pressure to the power system. The traditional flying plot detection algorithm has plenty of defects, such as low pertinence, low sensitivity and long sampling period. This paper proposes a new algorithm to identify flying plot by analyzing the wave form characteristics of sampling data. The traditional waveform recognition methods are combined in this algorithm. It has the concept of standard wave window and can distinguish flying plot in a short time. In addition, sine recovery algorithm is used to recover the flying plot. This paper uses PSCAD software to verify the validity of this algorithm. Simulation results show that the proposed method has high reliability.
文摘并网运行的交直流混合微网中,交流侧接入非线性负载会导致公共并网点(point of common coupling,PCC)处电流出现明显畸变。为避免引入额外有源滤波器装置,在基于综合惯量的互联变换器控制基础上,叠加准比例谐振控制器用于谐波补偿控制,通过公共并网点处电流反馈信号,实现电流正弦性和交直流侧功率平衡。同时,在谐波补偿环节引入多采率控制,解决了互联变换器低开关频率控制过程中的延时而导致的谐波重构误差问题,改善谐波补偿效果,并给出准比例谐振控制器参数的设计过程。基于Matlab/Sinmulink仿真实验结果表明所提方案稳态特性好,动态响应快,对负荷突变适应性好,控制算法简单可靠。