Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather an...Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather and climate phenomena.In the past few decades,dynamical numerical models have been the primary tools for predictability studies,achieving significant progress.Nowadays,with the advances in artificial intelligence(AI)techniques and accumulations of vast meteorological data,modeling weather and climate events using modern data-driven approaches is becoming trendy,where FourCastNet,Pangu-Weather,and GraphCast are successful pioneers.In this perspective article,we suggest AI models should not be limited to forecasting but be expanded to predictability studies,leveraging AI's advantages of high efficiency and self-contained optimization modules.To this end,we first remark that AI models should possess high simulation capability with fine spatiotemporal resolution for two kinds of predictability studies.AI models with high simulation capabilities comparable to numerical models can be considered to provide solutions to partial differential equations in a data-driven way.Then,we highlight several specific predictability issues with well-determined nonlinear optimization formulizations,which can be well-studied using AI models,holding significant scientific value.In addition,we advocate for the incorporation of AI models into the synergistic cycle of the cognition–observation–model paradigm.Comprehensive predictability studies have the potential to transform“big data”to“big and better data”and shift the focus from“AI for forecasts”to“AI for science”,ultimately advancing the development of the atmospheric and oceanic sciences.展开更多
Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,...Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,which is expressed by the recorded time multiplying a ratio coefficient.And then a time split model is proposed by expressing the acoustic ray traveling time as the recorded time pluses a perturbation time error.The theoretical differences between the proposed time bias compensation model and the time ratio model are analyzed.Under the new framework,sound speed perturbation models with optimal single-layer spatial gradient and multi-layer spatial gradients are developed to compensate for sound speed error in the complex cases.Numerical computation shows that the simple time split model keeps the same accuracy as some complicated models while considering the distribution of random error.Furthermore,multi-layer model can improve the positioning accuracy without putting the pressure on parametrization.展开更多
Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolu...Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.展开更多
This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor...This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor(PMSM) in d-q frame and its space-state equation are established. The slide model control method is used to estimate the electromotive force of PMSM under static frame, while the position of rotor and its actual speed are estimated by using phase loop lock(PLL) method. Next,using Lyapunov stability theorem, the asymptotical stability condition of the slide model observer is presented. Furthermore, based on the backstepping control theory, the PMSM rotor speed and current tracking backstepping controllers are designed, because such controllers display excellent speed tracking and anti-disturbance performance. Finally, Matlab simulation results show that the slide model observer can not only estimate the rotor position and speed of the PMSM accurately, but also ensure the asymptotical stability of the system and effective adjustment of rotor speed and current.展开更多
In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angu...In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angular observation model to integrate observations from UAV and mobile mapping vehicle platform,realizing a joint,coordinated observation operation from both air and ground.We develop a multi-source remote sensing data acquisition system to effectively acquire multi-angle data of complex urban scenes.Multi-source data fusion solves the missing data problem caused by occlusion and achieves accurate,rapid,and complete collection of holographic spatial and temporal information in complex urban scenes.We carried out an experiment on Baisha Town,Chongqing,China and obtained multi-sensor,multi-angle data from UAV and mobile mapping vehicle.We first extracted the point cloud from UAV and then integrated the UAV and mobile mapping vehicle point cloud.The inte-grated results combined both the characteristics of UAV and mobile mapping vehicle point cloud,confirming the practicability of the proposed joint data acquisition platform and the effectiveness of spatio-temporal-spectral-angular observation model.Compared with the observation from UAV or mobile mapping vehicle alone,the integrated system provides an effective data acquisition solution toward comprehensive urban monitoring.展开更多
Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currentl...Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.展开更多
The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation acc...The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation accuracy and therefore navigation accuracy.Additionally,the conventional observation model（COM）used by the filter may be divergent,which would result into some terrible accuracies of INS/GPS integration navigation in some cases.To improve the navigation accuracy,the linearization accuracy of the COM still needs further improvement.To deal with this issue,the observation model is modified with the linearization of the range and range rate equations in this paper.Compared with COM,the modified observation model（MOM）further considers the difference between the real user position and the position calculated by SINS.To verify the advantages of this model,INS/GPS integrated navigation simulation experiments are conducted with the usage of COM and MOM respectively.According to the simulation results,the positions（velocities）calculated using COM are divergent over time while the others using MOM are convergent,which demonstrates the higher linearization accuracy of MOM.展开更多
When there exists anisotropy in underground media elastic parameters of the observed coordinate possibly do not coincide with that of the natural coordinate. According to the theory that the density of potential energ...When there exists anisotropy in underground media elastic parameters of the observed coordinate possibly do not coincide with that of the natural coordinate. According to the theory that the density of potential energy, dissipating energy is independent of the coordinate, the relationship of elastic parameters between two coordinates is derived for two-phase anisotropic media. Then, pseudospectral method to solve wave equations of two-phase anisotropic media is derived. At last, we use this method to simulate wave propagation in two-phase anisotropic media four types of waves are observed in the snapshots, i.e., fast P wave and slow P wave, fast S wave and slow S wave. Shear wave splitting, SV wave cusps and elastic wave reflection and transmission are also observed.展开更多
The combination of spin-orbit coupling （SOC） and in-plane Zeeman field breaks time-reversal and inversion symmetries of Fermi gases and becomes a popular way to produce single plane wave Fulde-Ferrell （FF） superf...The combination of spin-orbit coupling （SOC） and in-plane Zeeman field breaks time-reversal and inversion symmetries of Fermi gases and becomes a popular way to produce single plane wave Fulde-Ferrell （FF） superfluid. However, atom loss and heating related to SOC have impeded the successful observation of FF state until now. In this work, we propose the realization of spin-balanced FF superfluid in a honeycomb lattice without SOC and the Zeeman field. A key ingredient of our scheme is generating complex hopping terms in original honeycomb lattices by periodical driving. In our model the ground state is always the FF state, thus the experimental observation has no need of fine tuning. The other advantages of our scheme are its simplicity and feasibility, and thus may open a new route for observing FF superfluids.展开更多
This paper presents a novel observer model that integrates quantum mechanics, relativity, idealism, and the simulation hypothesis to explain the quantum nature of the universe. The model posits a central server transm...This paper presents a novel observer model that integrates quantum mechanics, relativity, idealism, and the simulation hypothesis to explain the quantum nature of the universe. The model posits a central server transmitting multi-media frames to create observer-dependent realities. Key aspects include deriving frame rates, defining quantum reality, and establishing hierarchical observer structures. The model’s impact on quantum information theory and philosophical interpretations of reality are examined, with detailed discussions on information loss and recursive frame transmission in the appendices.展开更多
The geometric phase has become a fundamental concept in many fields of physics since it was revealed. Recently, the study of the geometric phase has attracted considerable attention in the context of quantum phase tra...The geometric phase has become a fundamental concept in many fields of physics since it was revealed. Recently, the study of the geometric phase has attracted considerable attention in the context of quantum phase transition, where the ground state properties of the system experience a dramatic change induced by a variation of an external parameter. In this work, we experimentally measure the ground-state geometric phase of the three-spin XY model by utilizing the nuclear magnetic resonance technique. The experimental results indicate that the geometric phase could be used as a fingerprint of the ground-state quantum phase transition of many-body systems.展开更多
The physical characteristics of the summer monsoon clouds were investigated. The results of a simple cloud model were compared with the aircraft cloud physical observations collected during the summer monsoon seasons ...The physical characteristics of the summer monsoon clouds were investigated. The results of a simple cloud model were compared with the aircraft cloud physical observations collected during the summer monsoon seasons of 1973, 1974, 1976 and 1981 in the Deccan Plateau region.The model predicted profiles of cloud liquid water content (LWC) are in agreement with the observed profiles. There is reasonable agreement between the model predicted cloud vertical thickness and observed rainfall.The observed cloud-drop spectra were found to be narrow and the concentration of drops with diameter > 20um is either low or absent on many occasions. In such clouds the rain-formation cannot take place under natural atmospheric conditions due to the absence of collision-coalescence process. A comparison of the model predicted and observed rainfall suggested that the precipitation efficiency in cumulus clouds of small vertical thickness could be as low as 20 per cent.The clouds forming in the Deccan Plateau region during the summer monsoon are, by and large, cumulus and strato-cumulus type. The vertical thickness of the cumulus clouds is in the range of 1.0-2.0 km. The LWC is found to be more in the region between 1.6-1.9 km A. S. L. , which corresponds to the level at almost 3 / 4 th of the total vertical thickness of the cloud and thereafter the LWC sharply decreased. Nearly 98 per cent of the tops of the low clouds in the region are below freezing level and the most frequent range of occurrence of these cloud-tops is in the range of 2.0-3.0 km A. S. L. The dominant physical mechanism of rain-formation in these summer monsoon clouds is the collision-coalescence process.展开更多
A new hybrid model rotor flux observer, based on a new voltage model, is presented. In the first place, the voltage model of an induction machine was constructed by using the modeling method discussed in this paper an...A new hybrid model rotor flux observer, based on a new voltage model, is presented. In the first place, the voltage model of an induction machine was constructed by using the modeling method discussed in this paper and then the current model using a flux feedback was adopted in this flux observer. Secondly, the two models were com- bined via a filter and then the rotor flux observer was established. In the M-T synchronous coordinate, the observer was analyzed theoretically and several important functions were derived. A comparison between the observer and the traditional models was made using Matlab software. The simulation results show that the observer model had a better performance than the traditional model.展开更多
This paper introduces the Advanced Observer Model (AOM), a novel framework that integrates classical mechanics, quantum mechanics, and relativity through the observer’s role in constructing reality. Central to the AO...This paper introduces the Advanced Observer Model (AOM), a novel framework that integrates classical mechanics, quantum mechanics, and relativity through the observer’s role in constructing reality. Central to the AOM is the Static Configuration/Dynamic Configuration (SC/DC) conjugate, which examines physical systems through the interaction between static spatial configurations and dynamic quantum states. The model introduces a Constant Frame Rate (CFR) to quantize time perception, providing a discrete model for time evolution in quantum systems. By modifying the Schrödinger equation with CFR, the AOM bridges quantum and classical physics, offering a unified interpretation where classical determinism and quantum uncertainty coexist. A key feature of the AOM is its energy scaling model, where energy grows exponentially with spatial dimensionality, following the relationshipE∝(π)n. This dimensional scaling connects the discrete time perception of the observer with both quantum and classical energy distributions, providing insights into the nature of higher-dimensional spaces. Additionally, the AOM posits that spacetime curvature arises from quantum interactions, shaped by the observer’s discrete time perception. The model emphasizes the observer’s consciousness as a co-creator of reality, offering new approaches to understanding the quantum-classical transition. While speculative, the AOM opens new avenues for addressing foundational questions in quantum mechanics, relativity, dimensionality, and the nature of reality.展开更多
This paper introduces a groundbreaking synthesis of fundamental quantum mechanics with the Advanced Observer Model (AOM), presenting a unified framework that reimagines the construction of reality. AOM highlights the ...This paper introduces a groundbreaking synthesis of fundamental quantum mechanics with the Advanced Observer Model (AOM), presenting a unified framework that reimagines the construction of reality. AOM highlights the pivotal role of the observer in shaping reality, where classical notions of time, space, and energy are reexamined through the quantum lens. By engaging with key quantum equations—such as the Schrödinger equation, Heisenberg uncertainty principle, and Dirac equation—the paper demonstrates how AOM unifies the probabilistic nature of quantum mechanics with the determinism of classical physics. Central to this exploration is the Sequence of Quantum States (SQS) and Constant Frame Rate (CFR), which align with concepts like quantum superposition, entanglement, and wave function collapse. The model’s implications extend to how observers perceive reality, proposing that interference patterns between wave functions form the foundation of observable phenomena. By offering a fresh perspective on the interplay between determinacy and indeterminacy, AOM lays a robust theoretical foundation for future inquiry into quantum physics and the philosophy of consciousness.展开更多
This paper presents the Advanced Observer Model (AOM), a groundbreaking conceptual framework designed to clarify the complex and often enigmatic nature of quantum mechanics. The AOM serves as a metaphorical lens, brin...This paper presents the Advanced Observer Model (AOM), a groundbreaking conceptual framework designed to clarify the complex and often enigmatic nature of quantum mechanics. The AOM serves as a metaphorical lens, bringing the elusive quantum realm into sharper focus by transforming its inherent uncertainty into a coherent, structured ‘Frame Stream’ that aids in the understanding of quantum phenomena. While the AOM offers conceptual simplicity and clarity, it recognizes the necessity of a rigorous theoretical foundation to address the fundamental uncertainties that lie at the core of quantum mechanics. This paper seeks to illuminate those theoretical ambiguities, bridging the gap between the abstract insights of the AOM and the intricate mathematical foundations of quantum theory. By integrating the conceptual clarity of the AOM with the theoretical intricacies of quantum mechanics, this work aspires to deepen our understanding of this fascinating and elusive field.展开更多
This paper presents a new random weighting estimation method for dynamic navigation positioning. This method adopts the concept of random weighting estimation to estimate the covariance matrices of system state noises...This paper presents a new random weighting estimation method for dynamic navigation positioning. This method adopts the concept of random weighting estimation to estimate the covariance matrices of system state noises and observation noises for controlling the disturbances of singular observations and the kinematic model errors. It satisfies the practical requirements of the residual vector and innovation vector to sufficiently utilize observation information, thus weakening the disturbing effect of the kinematic model error and observation model error on the state parameter estimation. Theories and algorithms of random weighting estimation are established for estimating the covariance matrices of observation residual vectors and innovation vec- tors. This random weighting estimation method provides an effective solution for improving the positioning accuracy in dynamic navigation. Experimental results show that compared with the Kalman filtering, the extended Kalman filtering and the adaptive windowing filtering, the proposed method can adaptively determine the covariance matrices of observation error and state error, effectively resist the disturbances caused by system error and observation error, and significantly improve the positioning accu- racy for dynamic navigation.展开更多
The meaning to research the potential of VLBI for geodetic applications is summarized. And the observation models and their related parameters of geodetic interest are investigated. Then, the principle and method of u...The meaning to research the potential of VLBI for geodetic applications is summarized. And the observation models and their related parameters of geodetic interest are investigated. Then, the principle and method of using the random model in VLBI data processing are investigated. With the world wide VLBI data from 2000-2004, the conditions to compute the parameters of geodetic interest are introduced, and so are the computing methods and processes. And the computed resuits of the parameters of geodetic interest are analyzed.展开更多
We propose a robust visual tracking framework based on particle filter to deal with the object appearance changes due to varying illumination, pose variantions, and occlusions. We mainly improve the observation model ...We propose a robust visual tracking framework based on particle filter to deal with the object appearance changes due to varying illumination, pose variantions, and occlusions. We mainly improve the observation model and re-sampling process in a particle filter. We use on-line updating appearance model, affine transformation, and M-estimation to construct an adaptive observation model. On-line updating appearance model can adapt to the changes of illumination partially. Affine transformation-based similarity measurement is introduced to tackle pose variantions, and M-estimation is used to handle the occluded object in computing observation likelihood. To take advantage of the most recent observation and produce a suboptimal Gaussian proposal distribution, we incorporate Kalman filter into a particle filter to enhance the performance of the resampling process. To estimate the posterior probability density properly with lower computational complexity, we only employ a single Kalman filter to propagate Gaussian distribution. Experimental results have demonstrated the effectiveness and robustness of the proposed algorithm by tracking visual objects in the recorded video sequences.展开更多
Atmospheric oxidizing capacity(AOC)is an essential driving force of troposphere chemistry and self-cleaning,but the definition of AOC and its quantitative representation remain uncertain.Driven by national demand for ...Atmospheric oxidizing capacity(AOC)is an essential driving force of troposphere chemistry and self-cleaning,but the definition of AOC and its quantitative representation remain uncertain.Driven by national demand for air pollution control in recent years,Chinese scholars have carried out studies on theories of atmospheric chemistry and have made considerable progress in AOC research.This paper will give a brief review of these developments.First,AOC indexes were established that represent apparent atmospheric oxidizing ability(AOIe)and potential atmospheric oxidizing ability(AOIp)based on aspects of macrothermodynamics and microdynamics,respectively.A closed study refined the quantitative contributions of heterogeneous chemistry to AOC in Beijing,and these AOC methods were further applied in Beijing-Tianjin-Hebei and key areas across the country.In addition,the detection of ground or vertical profiles for atmospheric OH·,HO_(2)·,NO_(3)·radicals and reservoir molecules can now be obtained with domestic instruments in diverse environments.Moreover,laboratory smoke chamber simulations revealed heterogeneous processes involving reactions of O_(3)and NO_(2),which are typical oxidants in the surface/interface atmosphere,and the evolutionary and budgetary implications of atmospheric oxidants reacting under multispecies,multiphase and multi-interface conditions were obtained.Finally,based on the GRAPES-CUACE adjoint model improved by Chinese scholars,simulations of key substances affecting atmospheric oxidation and secondary organic and inorganic aerosol formation have been optimized.Normalized numerical simulations of AOIe and AOIp were performed,and regional coordination of AOC was adjusted.An optimized plan for controlling O_(3)and PM2.5was analyzed by scenario simulation.展开更多
基金in part supported by the National Natural Science Foundation of China(Grant Nos.42288101,42405147 and 42475054)in part by the China National Postdoctoral Program for Innovative Talents(Grant No.BX20230071)。
文摘Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather and climate phenomena.In the past few decades,dynamical numerical models have been the primary tools for predictability studies,achieving significant progress.Nowadays,with the advances in artificial intelligence(AI)techniques and accumulations of vast meteorological data,modeling weather and climate events using modern data-driven approaches is becoming trendy,where FourCastNet,Pangu-Weather,and GraphCast are successful pioneers.In this perspective article,we suggest AI models should not be limited to forecasting but be expanded to predictability studies,leveraging AI's advantages of high efficiency and self-contained optimization modules.To this end,we first remark that AI models should possess high simulation capability with fine spatiotemporal resolution for two kinds of predictability studies.AI models with high simulation capabilities comparable to numerical models can be considered to provide solutions to partial differential equations in a data-driven way.Then,we highlight several specific predictability issues with well-determined nonlinear optimization formulizations,which can be well-studied using AI models,holding significant scientific value.In addition,we advocate for the incorporation of AI models into the synergistic cycle of the cognition–observation–model paradigm.Comprehensive predictability studies have the potential to transform“big data”to“big and better data”and shift the focus from“AI for forecasts”to“AI for science”,ultimately advancing the development of the atmospheric and oceanic sciences.
基金The National Natural Science Foundation of China under contract No.41931076the National Center for Basic Sciences Project under contract No.42388102the Laoshan Laboratory under contract No.LSKJ202205100.
文摘Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,which is expressed by the recorded time multiplying a ratio coefficient.And then a time split model is proposed by expressing the acoustic ray traveling time as the recorded time pluses a perturbation time error.The theoretical differences between the proposed time bias compensation model and the time ratio model are analyzed.Under the new framework,sound speed perturbation models with optimal single-layer spatial gradient and multi-layer spatial gradients are developed to compensate for sound speed error in the complex cases.Numerical computation shows that the simple time split model keeps the same accuracy as some complicated models while considering the distribution of random error.Furthermore,multi-layer model can improve the positioning accuracy without putting the pressure on parametrization.
基金This work is supported by the National Key Research and Development Program of China[grant number 2018YFB2100501]the Key Research and Development Program of Yunnan province in China[grant number 2018IB023]+2 种基金the Research Project from the Ministry of Natural Resources of China[grant number 4201⁃⁃240100123]the National Natural Science Foundation of China[grant numbers 41771452,41771454,41890820,and 41901340]the Natural Science Fund of Hubei Province in China[grant number 2018CFA007].
文摘Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.
基金supported by National Natural Science Foundation of China(Nos.61104072 and 11271309)
文摘This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor(PMSM) in d-q frame and its space-state equation are established. The slide model control method is used to estimate the electromotive force of PMSM under static frame, while the position of rotor and its actual speed are estimated by using phase loop lock(PLL) method. Next,using Lyapunov stability theorem, the asymptotical stability condition of the slide model observer is presented. Furthermore, based on the backstepping control theory, the PMSM rotor speed and current tracking backstepping controllers are designed, because such controllers display excellent speed tracking and anti-disturbance performance. Finally, Matlab simulation results show that the slide model observer can not only estimate the rotor position and speed of the PMSM accurately, but also ensure the asymptotical stability of the system and effective adjustment of rotor speed and current.
基金This work is supported by the National Natural Science Foundation of China[grant numbers 42090012,41771452,41771454,and 41901340].
文摘In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angular observation model to integrate observations from UAV and mobile mapping vehicle platform,realizing a joint,coordinated observation operation from both air and ground.We develop a multi-source remote sensing data acquisition system to effectively acquire multi-angle data of complex urban scenes.Multi-source data fusion solves the missing data problem caused by occlusion and achieves accurate,rapid,and complete collection of holographic spatial and temporal information in complex urban scenes.We carried out an experiment on Baisha Town,Chongqing,China and obtained multi-sensor,multi-angle data from UAV and mobile mapping vehicle.We first extracted the point cloud from UAV and then integrated the UAV and mobile mapping vehicle point cloud.The inte-grated results combined both the characteristics of UAV and mobile mapping vehicle point cloud,confirming the practicability of the proposed joint data acquisition platform and the effectiveness of spatio-temporal-spectral-angular observation model.Compared with the observation from UAV or mobile mapping vehicle alone,the integrated system provides an effective data acquisition solution toward comprehensive urban monitoring.
基金supported by National Natural Science Foundation of China,China(No.42004016)HuBei Natural Science Fund,China(No.2020CFB329)+1 种基金HuNan Natural Science Fund,China(No.2023JJ60559,2023JJ60560)the State Key Laboratory of Geodesy and Earth’s Dynamics self-deployment project,China(No.S21L6101)。
文摘Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.
基金Supported by the National Natural Science Foundation of China(61502257,41304031)
文摘The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation accuracy and therefore navigation accuracy.Additionally,the conventional observation model（COM）used by the filter may be divergent,which would result into some terrible accuracies of INS/GPS integration navigation in some cases.To improve the navigation accuracy,the linearization accuracy of the COM still needs further improvement.To deal with this issue,the observation model is modified with the linearization of the range and range rate equations in this paper.Compared with COM,the modified observation model（MOM）further considers the difference between the real user position and the position calculated by SINS.To verify the advantages of this model,INS/GPS integrated navigation simulation experiments are conducted with the usage of COM and MOM respectively.According to the simulation results,the positions（velocities）calculated using COM are divergent over time while the others using MOM are convergent,which demonstrates the higher linearization accuracy of MOM.
文摘When there exists anisotropy in underground media elastic parameters of the observed coordinate possibly do not coincide with that of the natural coordinate. According to the theory that the density of potential energy, dissipating energy is independent of the coordinate, the relationship of elastic parameters between two coordinates is derived for two-phase anisotropic media. Then, pseudospectral method to solve wave equations of two-phase anisotropic media is derived. At last, we use this method to simulate wave propagation in two-phase anisotropic media four types of waves are observed in the snapshots, i.e., fast P wave and slow P wave, fast S wave and slow S wave. Shear wave splitting, SV wave cusps and elastic wave reflection and transmission are also observed.
基金Supported by the Natural Science Foundation of Jiangsu Province under Grant No BK20130424the National Natural Science Foundation of China under Grant No 11547047
文摘The combination of spin-orbit coupling （SOC） and in-plane Zeeman field breaks time-reversal and inversion symmetries of Fermi gases and becomes a popular way to produce single plane wave Fulde-Ferrell （FF） superfluid. However, atom loss and heating related to SOC have impeded the successful observation of FF state until now. In this work, we propose the realization of spin-balanced FF superfluid in a honeycomb lattice without SOC and the Zeeman field. A key ingredient of our scheme is generating complex hopping terms in original honeycomb lattices by periodical driving. In our model the ground state is always the FF state, thus the experimental observation has no need of fine tuning. The other advantages of our scheme are its simplicity and feasibility, and thus may open a new route for observing FF superfluids.
文摘This paper presents a novel observer model that integrates quantum mechanics, relativity, idealism, and the simulation hypothesis to explain the quantum nature of the universe. The model posits a central server transmitting multi-media frames to create observer-dependent realities. Key aspects include deriving frame rates, defining quantum reality, and establishing hierarchical observer structures. The model’s impact on quantum information theory and philosophical interpretations of reality are examined, with detailed discussions on information loss and recursive frame transmission in the appendices.
基金Supported by the National Key Basic Research Program under Grant Nos 2013CB921800 and 2014CB848700the National Science Fund for Distinguished Young Scholars under Grant No 11425523+4 种基金the National Natural Science Foundation of China under Grant Nos 11375167,11227901,91021005 and 11575173the Strategic Priority Research Program(B)of the Chinese Academy of Sciences under Grant No XDB01030400the Research Fund for the Doctoral Program of Higher Education of China under Grant No 20113402110044the China Postdoctoral Science Foundationthe Fundamental Research Funds for the Central Universities
文摘The geometric phase has become a fundamental concept in many fields of physics since it was revealed. Recently, the study of the geometric phase has attracted considerable attention in the context of quantum phase transition, where the ground state properties of the system experience a dramatic change induced by a variation of an external parameter. In this work, we experimentally measure the ground-state geometric phase of the three-spin XY model by utilizing the nuclear magnetic resonance technique. The experimental results indicate that the geometric phase could be used as a fingerprint of the ground-state quantum phase transition of many-body systems.
文摘The physical characteristics of the summer monsoon clouds were investigated. The results of a simple cloud model were compared with the aircraft cloud physical observations collected during the summer monsoon seasons of 1973, 1974, 1976 and 1981 in the Deccan Plateau region.The model predicted profiles of cloud liquid water content (LWC) are in agreement with the observed profiles. There is reasonable agreement between the model predicted cloud vertical thickness and observed rainfall.The observed cloud-drop spectra were found to be narrow and the concentration of drops with diameter > 20um is either low or absent on many occasions. In such clouds the rain-formation cannot take place under natural atmospheric conditions due to the absence of collision-coalescence process. A comparison of the model predicted and observed rainfall suggested that the precipitation efficiency in cumulus clouds of small vertical thickness could be as low as 20 per cent.The clouds forming in the Deccan Plateau region during the summer monsoon are, by and large, cumulus and strato-cumulus type. The vertical thickness of the cumulus clouds is in the range of 1.0-2.0 km. The LWC is found to be more in the region between 1.6-1.9 km A. S. L. , which corresponds to the level at almost 3 / 4 th of the total vertical thickness of the cloud and thereafter the LWC sharply decreased. Nearly 98 per cent of the tops of the low clouds in the region are below freezing level and the most frequent range of occurrence of these cloud-tops is in the range of 2.0-3.0 km A. S. L. The dominant physical mechanism of rain-formation in these summer monsoon clouds is the collision-coalescence process.
基金Projects (00KJD470002, 03KJD470036) supported by the Natural Science Foundation of the Bureau of Education Jiangsu Province
文摘A new hybrid model rotor flux observer, based on a new voltage model, is presented. In the first place, the voltage model of an induction machine was constructed by using the modeling method discussed in this paper and then the current model using a flux feedback was adopted in this flux observer. Secondly, the two models were com- bined via a filter and then the rotor flux observer was established. In the M-T synchronous coordinate, the observer was analyzed theoretically and several important functions were derived. A comparison between the observer and the traditional models was made using Matlab software. The simulation results show that the observer model had a better performance than the traditional model.
文摘This paper introduces the Advanced Observer Model (AOM), a novel framework that integrates classical mechanics, quantum mechanics, and relativity through the observer’s role in constructing reality. Central to the AOM is the Static Configuration/Dynamic Configuration (SC/DC) conjugate, which examines physical systems through the interaction between static spatial configurations and dynamic quantum states. The model introduces a Constant Frame Rate (CFR) to quantize time perception, providing a discrete model for time evolution in quantum systems. By modifying the Schrödinger equation with CFR, the AOM bridges quantum and classical physics, offering a unified interpretation where classical determinism and quantum uncertainty coexist. A key feature of the AOM is its energy scaling model, where energy grows exponentially with spatial dimensionality, following the relationshipE∝(π)n. This dimensional scaling connects the discrete time perception of the observer with both quantum and classical energy distributions, providing insights into the nature of higher-dimensional spaces. Additionally, the AOM posits that spacetime curvature arises from quantum interactions, shaped by the observer’s discrete time perception. The model emphasizes the observer’s consciousness as a co-creator of reality, offering new approaches to understanding the quantum-classical transition. While speculative, the AOM opens new avenues for addressing foundational questions in quantum mechanics, relativity, dimensionality, and the nature of reality.
文摘This paper introduces a groundbreaking synthesis of fundamental quantum mechanics with the Advanced Observer Model (AOM), presenting a unified framework that reimagines the construction of reality. AOM highlights the pivotal role of the observer in shaping reality, where classical notions of time, space, and energy are reexamined through the quantum lens. By engaging with key quantum equations—such as the Schrödinger equation, Heisenberg uncertainty principle, and Dirac equation—the paper demonstrates how AOM unifies the probabilistic nature of quantum mechanics with the determinism of classical physics. Central to this exploration is the Sequence of Quantum States (SQS) and Constant Frame Rate (CFR), which align with concepts like quantum superposition, entanglement, and wave function collapse. The model’s implications extend to how observers perceive reality, proposing that interference patterns between wave functions form the foundation of observable phenomena. By offering a fresh perspective on the interplay between determinacy and indeterminacy, AOM lays a robust theoretical foundation for future inquiry into quantum physics and the philosophy of consciousness.
文摘This paper presents the Advanced Observer Model (AOM), a groundbreaking conceptual framework designed to clarify the complex and often enigmatic nature of quantum mechanics. The AOM serves as a metaphorical lens, bringing the elusive quantum realm into sharper focus by transforming its inherent uncertainty into a coherent, structured ‘Frame Stream’ that aids in the understanding of quantum phenomena. While the AOM offers conceptual simplicity and clarity, it recognizes the necessity of a rigorous theoretical foundation to address the fundamental uncertainties that lie at the core of quantum mechanics. This paper seeks to illuminate those theoretical ambiguities, bridging the gap between the abstract insights of the AOM and the intricate mathematical foundations of quantum theory. By integrating the conceptual clarity of the AOM with the theoretical intricacies of quantum mechanics, this work aspires to deepen our understanding of this fascinating and elusive field.
基金National Natural Science Foundation of China(60574034)Aeronautical Science Foundation of China(20080818004)
文摘This paper presents a new random weighting estimation method for dynamic navigation positioning. This method adopts the concept of random weighting estimation to estimate the covariance matrices of system state noises and observation noises for controlling the disturbances of singular observations and the kinematic model errors. It satisfies the practical requirements of the residual vector and innovation vector to sufficiently utilize observation information, thus weakening the disturbing effect of the kinematic model error and observation model error on the state parameter estimation. Theories and algorithms of random weighting estimation are established for estimating the covariance matrices of observation residual vectors and innovation vec- tors. This random weighting estimation method provides an effective solution for improving the positioning accuracy in dynamic navigation. Experimental results show that compared with the Kalman filtering, the extended Kalman filtering and the adaptive windowing filtering, the proposed method can adaptively determine the covariance matrices of observation error and state error, effectively resist the disturbances caused by system error and observation error, and significantly improve the positioning accu- racy for dynamic navigation.
基金Funded by the National 973 Program of China (No.2006CB701301)the Project of University Education and Research of HubeiProvince (No.20053039).
文摘The meaning to research the potential of VLBI for geodetic applications is summarized. And the observation models and their related parameters of geodetic interest are investigated. Then, the principle and method of using the random model in VLBI data processing are investigated. With the world wide VLBI data from 2000-2004, the conditions to compute the parameters of geodetic interest are introduced, and so are the computing methods and processes. And the computed resuits of the parameters of geodetic interest are analyzed.
基金supported by National Natural Science Foundation of China (No.40627001)the 985 Innovation Project on Information Technique of Xiamen University (2004–2008)
文摘We propose a robust visual tracking framework based on particle filter to deal with the object appearance changes due to varying illumination, pose variantions, and occlusions. We mainly improve the observation model and re-sampling process in a particle filter. We use on-line updating appearance model, affine transformation, and M-estimation to construct an adaptive observation model. On-line updating appearance model can adapt to the changes of illumination partially. Affine transformation-based similarity measurement is introduced to tackle pose variantions, and M-estimation is used to handle the occluded object in computing observation likelihood. To take advantage of the most recent observation and produce a suboptimal Gaussian proposal distribution, we incorporate Kalman filter into a particle filter to enhance the performance of the resampling process. To estimate the posterior probability density properly with lower computational complexity, we only employ a single Kalman filter to propagate Gaussian distribution. Experimental results have demonstrated the effectiveness and robustness of the proposed algorithm by tracking visual objects in the recorded video sequences.
基金supported by the Ministry of Science and Technology of the People’s Republic of China(No.2017YFC0210000)the Young Talent Project of the Center for Excellence in Regional Atmospheric Environment,CAS(No.CERAE202002)+1 种基金the National Natural Science Foundation of China(No.41705110)Beijing Major Science and Technology Project(No.Z211100004321006)。
文摘Atmospheric oxidizing capacity(AOC)is an essential driving force of troposphere chemistry and self-cleaning,but the definition of AOC and its quantitative representation remain uncertain.Driven by national demand for air pollution control in recent years,Chinese scholars have carried out studies on theories of atmospheric chemistry and have made considerable progress in AOC research.This paper will give a brief review of these developments.First,AOC indexes were established that represent apparent atmospheric oxidizing ability(AOIe)and potential atmospheric oxidizing ability(AOIp)based on aspects of macrothermodynamics and microdynamics,respectively.A closed study refined the quantitative contributions of heterogeneous chemistry to AOC in Beijing,and these AOC methods were further applied in Beijing-Tianjin-Hebei and key areas across the country.In addition,the detection of ground or vertical profiles for atmospheric OH·,HO_(2)·,NO_(3)·radicals and reservoir molecules can now be obtained with domestic instruments in diverse environments.Moreover,laboratory smoke chamber simulations revealed heterogeneous processes involving reactions of O_(3)and NO_(2),which are typical oxidants in the surface/interface atmosphere,and the evolutionary and budgetary implications of atmospheric oxidants reacting under multispecies,multiphase and multi-interface conditions were obtained.Finally,based on the GRAPES-CUACE adjoint model improved by Chinese scholars,simulations of key substances affecting atmospheric oxidation and secondary organic and inorganic aerosol formation have been optimized.Normalized numerical simulations of AOIe and AOIp were performed,and regional coordination of AOC was adjusted.An optimized plan for controlling O_(3)and PM2.5was analyzed by scenario simulation.
