High-precision day-ahead short-term photovoltaic(PV)output forecasting is essential in PV integration to the smart distribution networks and multi-energy system,and provides the foundation for the security,stability,a...High-precision day-ahead short-term photovoltaic(PV)output forecasting is essential in PV integration to the smart distribution networks and multi-energy system,and provides the foundation for the security,stability,and economic operation of PV systems.This paper proposes a hybrid model based on principal component analysis,grey wolf optimization and generalized regression neural network(PCA-GWO-GRNN)for day-ahead short-term PV output forecasting,considering the features of multiple influencing factors and strong uncertainty.This paper first uses the PCA to reduce the dimension of meteorological features.Then,the high-precision day-ahead short-term PV output forecasting based on GWO-GRNN model is realized.GRNN is used to regressively analyze the input features after dimension reduction,and the parameter of GRNN is optimized by using GWO,which has strong global searching ability and fast convergence.The proposed PCA-GWO-GRNN model effectively achieves a high precision in day-ahead shortterm PV output forecasting,which is demonstrated in a case study on a real PV plant in Jiangsu province,China.The results have validated the accuracy and applicability of the proposed model in real scenarios.展开更多
Ice flashover,lightning flashover and bird damage are the main reasons that cause transmission facility failure.The impact of these environmental factors on the operational risk levels of power systems should be taken...Ice flashover,lightning flashover and bird damage are the main reasons that cause transmission facility failure.The impact of these environmental factors on the operational risk levels of power systems should be taken into account in power system maintenance scheduling and operation planning.This paper studies the midshort-term risk assessment methodology considering the impact of the external environment.The relationship model between natural disasters and transmission lines is presented.The conditional outage rate model and the sampling technique are then proposed considering the correlated outage of multiple transmission lines when a disaster happens.The framework of the mid-short-term risk assessment model is outlined.A test case of Jiangxi provincial power grid validates the proposed model.The results show that the model can quantify the impact of disasters on the forced outage rate of transmission component and their outage correlation,and thus effectively revealing the mid-short-term risk of power systems.The model can facilitate a more strategic decision-making on maintenance scheduling and operation planning of power systems.展开更多
Industrial Control Systems(ICSs)are the lifeline of a country.Therefore,the anomaly detection of ICS traffic is an important endeavor.This paper proposes a model based on a deep residual Convolution Neural Network(CNN...Industrial Control Systems(ICSs)are the lifeline of a country.Therefore,the anomaly detection of ICS traffic is an important endeavor.This paper proposes a model based on a deep residual Convolution Neural Network(CNN)to prevent gradient explosion or gradient disappearance and guarantee accuracy.The developed methodology addresses two limitations:most traditional machine learning methods can only detect known network attacks and deep learning algorithms require a long time to train.The utilization of transfer learning under the modification of the existing residual CNN structure guarantees the detection of unknown attacks.One-dimensional ICS flow data are converted into two-dimensional grayscale images to take full advantage of the features of CNN.Results show that the proposed method achieves a high score and solves the time problem associated with deep learning model training.The model can give reliable predictions for unknown or differently distributed abnormal data through short-term training.Thus,the proposed model ensures the safety of ICSs and verifies the feasibility of transfer learning for ICS anomaly detection.展开更多
Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the m...Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the means.It is a revolutionary leap in the research of geoscience knowledge discovery from the traditional encyclopedic discipline knowledge system to the computer-understandable and operable knowledge graph.Based on adopting the graph pattern of general knowledge representation,the geoscience knowledge graph expands the unique spatiotemporal features to the Geoscience knowledge,and integrates geoscience knowledge elements,such as map,text,and number,to establish an all-domain geoscience knowledge representation model.A federated,crowd intelligence-based collaborative method of constructing the geoscience knowledge graph is developed here,which realizes the construction of high-quality professional knowledge graph in collaboration with global geo-scientists.We also develop a method for constructing a dynamic knowledge graph of multi-modal geoscience data based on in-depth text analysis,which extracts geoscience knowledge from massive geoscience literature to construct the latest and most complete dynamic geoscience knowledge graph.A comprehensive and systematic geoscience knowledge graph can not only deepen the existing geoscience big data analysis,but also advance the construction of the high-precision geological time scale driven by big data,the compilation of intelligent maps driven by rules and data,and the geoscience knowledge evolution and reasoning analysis,among others.It will further expand the new directions of geoscience research driven by both data and knowledge,break new ground where geoscience,information science,and data science converge,realize the original innovation of the geoscience research and achieve major theoretical breakthroughs in the spatiotemporal big data research.展开更多
In this paper, the data-based control problem is investigated for a class of networked nonlinear systems with measurement noise as well as packet dropouts in the feedback and forward channels. The measurement noise an...In this paper, the data-based control problem is investigated for a class of networked nonlinear systems with measurement noise as well as packet dropouts in the feedback and forward channels. The measurement noise and the number of consecutive packet dropouts in both channels are assumed to be random but bounded. A data-based networked predictive control method is proposed, in which a sequence of control increment predictions are calculated in the controller based on the measured output error, and based on the control increment predictions received by the actuator, a proper control action is obtained and applied to the plant according to the real-time number of consecutive packet dropouts at each sampling instant. Then the stability analysis is performed for the networked closedloop system. Finally, the effectiveness of the proposed method is illustrated by a numerical example.展开更多
Recently, the development of modern vehicles has brought about aggressive integration and miniaturization of on-board electrical and electronic devices. It will lead to exponential growth in both the overall waste hea...Recently, the development of modern vehicles has brought about aggressive integration and miniaturization of on-board electrical and electronic devices. It will lead to exponential growth in both the overall waste heat and heat flux to be dissipated to maintain the devices within a safe temperature range. However, both the total heat sinks aboard and the cooling capacity of currently utilized thermal control strategy are severely limited, which threatens the lifetime of the on-board equipment and even the entire flight system and shrink the vehicle’s flight time and range. Facing these thermal challenges, the USA proposed the program of "INVENT" to maximize utilities of the available heat sinks and enhance the cooling ability of thermal control strategies. Following the efforts done by the USA researchers, scientists in China fought their ways to develop thermal management technologies for Chinese advanced energy-optimized airplanes and spacecraft. This paper elaborates the available on-board heat sinks and aerospace thermal management systems using both active and passive technologies not confined to the technology in China. Subsequently, active thermal management technologies in China including fuel thermal management system, environment control system, non-fuel liquid cooling strategy are reviewed. At last, space thermal control technologies used in Chinese Space Station and Chang’e-3 and to be used in Chang’e-5 are introduced.Key issues to be solved are also identified, which could facilitate the development of aerospace thermal control techniques across the world.展开更多
Due to low investment cost and high reliability,a new scheme called DR-HVDC(Diode Rectifier based HVDC)transmission was recently proposed for grid integration of large offshore wind farms.However,in this scheme,the ap...Due to low investment cost and high reliability,a new scheme called DR-HVDC(Diode Rectifier based HVDC)transmission was recently proposed for grid integration of large offshore wind farms.However,in this scheme,the application of conventional control strategies for stability operation face several challenges due to the uncontrollability of the DR.In this paper,a coordinated control strategy of offshore wind farms using the DR-HVDC transmission technology to connect with the onshore grid,is investigated.A novel coordinated control strategy for DR-HVDC is proposed based on the analysis of the DC current control ability of the full-bridge-based modular multilevel converter(FB-MMC)at the onshore station and the input and output characteristics of the diode rectifier at the offshore.Considering the characteristics of operation stability and decoupling between reactive power and active power,a simplified design based on double-loop droop control for offshore AC voltage is proposed after power flow and voltage–current(I–V)characteristics of the offshore wind farm being analyzed.Furthermore,the impact of onshore AC fault to offshore wind farm is analyzed,and a fast fault detection and protection strategy without relying on communication is proposed.Case studies carried out by PSCAD/EMTDC verify the effectiveness of the proposed control strategy for the start up,power fluctuation,and onshore and offshore fault conditions.展开更多
In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management...In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management,and control(CMC).We describe the historical development of complex system science and analyze the limitations of human intelligence and machine intelligence.The need for using human-machine HAI in complex systems is then explained in detail.The concept of“mutually trustworthy HM-KA”mechanism is proposed to tackle the CMC challenge,and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid dispatch.It is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.展开更多
Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and ...Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and timely. First, FCM clustering is employed to classify the data into different clusters, which helps to estimate whether there is a fault and how many fault types there are. If fault signals exist, the fault vibration signals are then demodulated and decomposed into different frequency bands by MMEMD in order to be analyzed further. In order to overcome the mode mixing defect of empirical mode decomposition (EMD), a novel method called MMEMD is proposed. It is an improvement to masking empirical mode decomposition (MEMD). By adding multi-masking signals to the signals to be decomposed in different levels, it can restrain low-frequency components from mixing in highfrequency components effectively in the sifting process and then suppress the mode mixing. It has the advantages of easy implementation and strong ability of suppressing modal mixing. The fault type is determined by Hilbert envelope finally. The results of simulation signal decomposition showed the high performance of MMEMD. Experiments of bearing fault diagnosis in wind turbine bearing fault diagnosis proved the validity and high accuracy of the new method.展开更多
Hydrogen production from renewable energy sources(RESs)is one of the effective ways to achieve carbon peak and carbon neutralization.In order to ensure the efficient,reliable and stable operation of the DC microgrid(M...Hydrogen production from renewable energy sources(RESs)is one of the effective ways to achieve carbon peak and carbon neutralization.In order to ensure the efficient,reliable and stable operation of the DC microgrid(MG)with an electric-hydrogen hybrid energy storage system(ESS),the operational constraints and static dynamic characteristics of a hydrogen energy storage system(HESS)needs to be fully considered.First,different hydrogen production systems,using water electrolysis are compared,and the modeling method of the electrolyzer is summarized.The operational control architecture of the DC MG with electric-hydrogen is analyzed.Combined with the working characteristics of the alkaline electrolyzer,the influence of hydrogen energy storage access on the operational mode of the DC MG is analyzed.The operational control strategies of the DC MG with electric-hydrogen hybrid ESS are classified and analyzed from four different aspects:static and dynamic characteristics of the hydrogen energy storage system,power distribution of the electric-hydrogen hybrid ESS and the efficiency optimization of hydrogen energy storage.Finally,the advantages of a modular hydrogen production system(HPS)are described,and the technical problems and research directions in the future are discussed.展开更多
The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature. First, the so-called stochastic LaSalle theory is...The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature. First, the so-called stochastic LaSalle theory is extended to some extent, and accordingly, the results of global ultimate boundedness for stochastic nonlinear systems are developed. Next, a new design scheme of fuzzy adaptive control is proposed. The advantage of it is that it does not require priori knowledge of virtual control gain function sign, which is usually demanded in many designs. At the same time, the track performance of closed-loop systems is improved by adaptive modifying the estimated error upper bound. By theoretical analysis, the signals of closed-loop systems are globally ultimately bounded in probability and the track error converges to a small residual set around the origin in 4th-power expectation.展开更多
Digital twin is currently undergoing a significant transformation from the conceptual and theoretical research phase to the implementation and application phase.However,a universally adaptable research and development...Digital twin is currently undergoing a significant transformation from the conceptual and theoretical research phase to the implementation and application phase.However,a universally adaptable research and development platform for digital twin is critically needed to meet the development requirements.Specifically,a publicly accessible simulation,testing,and validation platform which can support digital twin model building,data processing,algorithm design,configuration,etc.,is urgently required for researchers.Furthermore,for developers from the industry,a lowcode development platform that can offer a customizable suite of functions such as model creation,data management,protocol configuration,and visualization is urgently needed.Meanwhile,for enterprise users,there is a lack of an application management platform that can be configured and migrated for various application scenarios,functions,and modes.Therefore,based on the system research of digital twin theories and key technologies by the authors(such as the five-dimension digital twin model,digital twin modeling and digital twin data theory,digital twin standards,and so on),a digital twin software platform reference architecture,namely make Twin,is proposed and designed,as well as its ten core functions.The workflow of the make Twin and the interaction mechanisms among its core functions are described.Finally,a digital twin application system for a chemical fiber textile shop floor(CFTS)which was developed according to make Twin,is introduced,which validates the proposed reference architecture.展开更多
A set of system based on personal computer for the bi-directional reflectance distribution function (BRDF) measurement was developed, whose laser wavelengths cover 0.6328, 1.34, 3.39, and 10.6 μm from visible to infr...A set of system based on personal computer for the bi-directional reflectance distribution function (BRDF) measurement was developed, whose laser wavelengths cover 0.6328, 1.34, 3.39, and 10.6 μm from visible to infrared. Stray light in BRDF measurement system was analyzed. It can be reduced and suppressed by the design of the system light path in BRDF measurement system, the choice of the measuring scheme, the processing to the optoelectronic signal, and the radiation control of the optical components and mechanical equipments. So the minimum measurable value of BRDF is less than 10-5/sr.展开更多
NiCr–Cr3C2 metal–ceramic composite coating is commonly produced on metal substrate by laser cladding to be used as wear-resistant coating under medium- or high-temperature working conditions.The coating has high har...NiCr–Cr3C2 metal–ceramic composite coating is commonly produced on metal substrate by laser cladding to be used as wear-resistant coating under medium- or high-temperature working conditions.The coating has high hardness, generally over three times that of the substrate.In order to make the hardness increase gradually from substrate to coating surface, the nickel-based alloy Ni45 was chosen as the transition layer and Ni Cr–Cr3C2 coating was indirectly cladded on 20Cr2Ni4 A substrate.Microstructure and composition of the coating were characterized by scanning electron microscope(SEM), energy-dispersive spectroscopy(EDS) and X-ray diffraction(XRD).Microhardness of the cross section of the coating was measured.Friction and wear behavior of Ni Cr–Cr3C2coating and substrate were investigated through sliding against the Si C ball at 20, 100 and 300 °C.The morphologies of worn surfaces were analyzed by SEM and EDS.The results show that the hardness of Ni45 transition layer is between that of the substrate and Ni Cr–Cr3C2coating, which avoids hardness jump and stress concentration of the coating.Ni Cr–Cr3C2coating contains hard phases of Cr3C2 and Cr7C3which enhance the wear resistance.With thetemperature increasing, friction coefficient and wear rate of the substrate increase significantly.Compared with the substrate, Ni Cr–Cr3C2coating has lower friction coefficient and wear rate at 100 and 300 °C, which verifies the good wear resistance of NiCr–Cr3C2 coating.展开更多
Optical imaging through or inside scattering media, such as multimode fiber and biological tissues, has a significant impact in biomedicine yet is considered challenging due to the strong scattering nature of light. I...Optical imaging through or inside scattering media, such as multimode fiber and biological tissues, has a significant impact in biomedicine yet is considered challenging due to the strong scattering nature of light. In the past decade, promising progress has been made in the field, largely benefiting from the invention of iterative optical wavefront shaping, with which deep-tissue high-resolution optical focusing and hence imaging becomes possible. Most of the reported iterative algorithms can overcome small perturbations on the noise level but fail to effectively adapt beyond the noise level, e.g., sudden strong perturbations. Reoptimizations are usually needed for significant decorrelation to the medium since these algorithms heavily rely on the optimization performance in the previous iterations. Such ineffectiveness is probably due to the absence of a metric that can gauge the deviation of the instant wavefront from the optimum compensation based on the concurrently measured optical focusing.In this study, a square rule of binary-amplitude modulation, directly relating the measured focusing performance with the error in the optimized wavefront, is theoretically proved and experimentally validated. With this simple rule, it is feasible to quantify how many pixels on the spatial light modulator incorrectly modulate the wavefront for the instant status of the medium or the whole system. As an example of application, we propose a novel algorithm, the dynamic mutation algorithm, which has high adaptability against perturbations by probing how far the optimization has gone toward the theoretically optimal performance. The diminished focus of scattered light can be effectively recovered when perturbations to the medium cause a significant drop in the focusing performance, which no existing algorithms can achieve due to their inherent strong dependence on previous optimizations. With further improvement, the square rule and the new algorithm may boost or inspire many applications, such as high-resolution optical imag展开更多
Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is expected.With conventional fossil-fueled synchronous generators in the transmission network being replaced ...Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is expected.With conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power systems.New analysis and control methods are needed for power systems to cope with the ongoing transformation.In the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power systems.Specifically,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.展开更多
A sliding mode control design for a miniature unmanned helicopter is presented. The control objective is to let the helicopter track some predefined velocity and yaw trajectories. A new sliding mode control design met...A sliding mode control design for a miniature unmanned helicopter is presented. The control objective is to let the helicopter track some predefined velocity and yaw trajectories. A new sliding mode control design method is developed based on a linearized dynamic model. In order to facilitate the control design, the helicopter＇s dynamic model is divided into two subsystems,such as the longitudinal-lateral and the heading-heave subsystem. The proposed controller employs sliding mode control technique to compensate for the immeasurable flapping angles＇ dynamic effects and external disturbances. The global asymptotic stability（GAS） of the closed-loop system is proved by the Lyapunov based stability analysis. Numerical simulations demonstrate that the proposed controller can achieve superior tracking performance compared with the proportionalintegral-derivative（PID） and linear-quadratic regulator（LQR） cascaded controller in the presence of wind gust disturbances.展开更多
基金supported by the National Key Research and Development Program of China(No.2018YFB1500800)the National Natural Science Foundation of China(No.51807134)
文摘High-precision day-ahead short-term photovoltaic(PV)output forecasting is essential in PV integration to the smart distribution networks and multi-energy system,and provides the foundation for the security,stability,and economic operation of PV systems.This paper proposes a hybrid model based on principal component analysis,grey wolf optimization and generalized regression neural network(PCA-GWO-GRNN)for day-ahead short-term PV output forecasting,considering the features of multiple influencing factors and strong uncertainty.This paper first uses the PCA to reduce the dimension of meteorological features.Then,the high-precision day-ahead short-term PV output forecasting based on GWO-GRNN model is realized.GRNN is used to regressively analyze the input features after dimension reduction,and the parameter of GRNN is optimized by using GWO,which has strong global searching ability and fast convergence.The proposed PCA-GWO-GRNN model effectively achieves a high precision in day-ahead shortterm PV output forecasting,which is demonstrated in a case study on a real PV plant in Jiangsu province,China.The results have validated the accuracy and applicability of the proposed model in real scenarios.
基金supported in part by National Natural Science Foundation of China(61533017,61273140,61304079,61374105,61379099,61233001)Fundamental Research Funds for the Central Universities(FRF-TP-15-056A3)the Open Research Project from SKLMCCS(20150104)
基金This work was supported by Jiangxi Electric Power Corporation Key Technical Project(No.201250601).
文摘Ice flashover,lightning flashover and bird damage are the main reasons that cause transmission facility failure.The impact of these environmental factors on the operational risk levels of power systems should be taken into account in power system maintenance scheduling and operation planning.This paper studies the midshort-term risk assessment methodology considering the impact of the external environment.The relationship model between natural disasters and transmission lines is presented.The conditional outage rate model and the sampling technique are then proposed considering the correlated outage of multiple transmission lines when a disaster happens.The framework of the mid-short-term risk assessment model is outlined.A test case of Jiangxi provincial power grid validates the proposed model.The results show that the model can quantify the impact of disasters on the forced outage rate of transmission component and their outage correlation,and thus effectively revealing the mid-short-term risk of power systems.The model can facilitate a more strategic decision-making on maintenance scheduling and operation planning of power systems.
基金supported in part by 2018 industrial Internet innovation and development project“Construction of Industrial Internet Security Standard System and Test and Verification Environment”in part by the National Industrial Internet Security Public Service Platform+2 种基金in part by the Fundamental Research Funds for the Central Universities(Nos.FRF-BD-19-012A and FRFTP-19-005A3)in part by the National Natural Science Foundation of China(Nos.81961138010,U1736117,and U1836106)in part by the Technological Innovation Foundation of Shunde Graduate School,University of Science and Technology Beijing(No.BK19BF006)。
文摘Industrial Control Systems(ICSs)are the lifeline of a country.Therefore,the anomaly detection of ICS traffic is an important endeavor.This paper proposes a model based on a deep residual Convolution Neural Network(CNN)to prevent gradient explosion or gradient disappearance and guarantee accuracy.The developed methodology addresses two limitations:most traditional machine learning methods can only detect known network attacks and deep learning algorithms require a long time to train.The utilization of transfer learning under the modification of the existing residual CNN structure guarantees the detection of unknown attacks.One-dimensional ICS flow data are converted into two-dimensional grayscale images to take full advantage of the features of CNN.Results show that the proposed method achieves a high score and solves the time problem associated with deep learning model training.The model can give reliable predictions for unknown or differently distributed abnormal data through short-term training.Thus,the proposed model ensures the safety of ICSs and verifies the feasibility of transfer learning for ICS anomaly detection.
基金supported by the National Natural Science Foundation of China(Grant Nos.41421001,42050101,and 42050105)。
文摘Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the means.It is a revolutionary leap in the research of geoscience knowledge discovery from the traditional encyclopedic discipline knowledge system to the computer-understandable and operable knowledge graph.Based on adopting the graph pattern of general knowledge representation,the geoscience knowledge graph expands the unique spatiotemporal features to the Geoscience knowledge,and integrates geoscience knowledge elements,such as map,text,and number,to establish an all-domain geoscience knowledge representation model.A federated,crowd intelligence-based collaborative method of constructing the geoscience knowledge graph is developed here,which realizes the construction of high-quality professional knowledge graph in collaboration with global geo-scientists.We also develop a method for constructing a dynamic knowledge graph of multi-modal geoscience data based on in-depth text analysis,which extracts geoscience knowledge from massive geoscience literature to construct the latest and most complete dynamic geoscience knowledge graph.A comprehensive and systematic geoscience knowledge graph can not only deepen the existing geoscience big data analysis,but also advance the construction of the high-precision geological time scale driven by big data,the compilation of intelligent maps driven by rules and data,and the geoscience knowledge evolution and reasoning analysis,among others.It will further expand the new directions of geoscience research driven by both data and knowledge,break new ground where geoscience,information science,and data science converge,realize the original innovation of the geoscience research and achieve major theoretical breakthroughs in the spatiotemporal big data research.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.61673023,61203230,61273104,61333003,61210012,and 61490701the Beijing Municipal Natural Science Foundation under Grant No.4152014+3 种基金the Great Wall Scholar Candidate Training Program of North China University of Technology(NCUT)the Excellent Youth Scholar Nurturing Program of NCUTthe Outstanding Young Scientist Award Foundation of Shandong Province of China under Grant No.BS2013DX015the Research Fund for the Taishan Scholar Project of Shandong Province of China
文摘In this paper, the data-based control problem is investigated for a class of networked nonlinear systems with measurement noise as well as packet dropouts in the feedback and forward channels. The measurement noise and the number of consecutive packet dropouts in both channels are assumed to be random but bounded. A data-based networked predictive control method is proposed, in which a sequence of control increment predictions are calculated in the controller based on the measured output error, and based on the control increment predictions received by the actuator, a proper control action is obtained and applied to the plant according to the real-time number of consecutive packet dropouts at each sampling instant. Then the stability analysis is performed for the networked closedloop system. Finally, the effectiveness of the proposed method is illustrated by a numerical example.
基金supported by the Starting Foundation for Young Researchers in Yangzhou Universityfunded by the Chinese Postdoctoral Science Foundation (No. 2020M671618)。
文摘Recently, the development of modern vehicles has brought about aggressive integration and miniaturization of on-board electrical and electronic devices. It will lead to exponential growth in both the overall waste heat and heat flux to be dissipated to maintain the devices within a safe temperature range. However, both the total heat sinks aboard and the cooling capacity of currently utilized thermal control strategy are severely limited, which threatens the lifetime of the on-board equipment and even the entire flight system and shrink the vehicle’s flight time and range. Facing these thermal challenges, the USA proposed the program of "INVENT" to maximize utilities of the available heat sinks and enhance the cooling ability of thermal control strategies. Following the efforts done by the USA researchers, scientists in China fought their ways to develop thermal management technologies for Chinese advanced energy-optimized airplanes and spacecraft. This paper elaborates the available on-board heat sinks and aerospace thermal management systems using both active and passive technologies not confined to the technology in China. Subsequently, active thermal management technologies in China including fuel thermal management system, environment control system, non-fuel liquid cooling strategy are reviewed. At last, space thermal control technologies used in Chinese Space Station and Chang’e-3 and to be used in Chang’e-5 are introduced.Key issues to be solved are also identified, which could facilitate the development of aerospace thermal control techniques across the world.
基金supported by State Grid Science and Technology Project“Study on Key Technologies of Large Scale Offshore Wind Power Integrating with Onshore Grid”(4000-202055045A-0-0-00)
文摘Due to low investment cost and high reliability,a new scheme called DR-HVDC(Diode Rectifier based HVDC)transmission was recently proposed for grid integration of large offshore wind farms.However,in this scheme,the application of conventional control strategies for stability operation face several challenges due to the uncontrollability of the DR.In this paper,a coordinated control strategy of offshore wind farms using the DR-HVDC transmission technology to connect with the onshore grid,is investigated.A novel coordinated control strategy for DR-HVDC is proposed based on the analysis of the DC current control ability of the full-bridge-based modular multilevel converter(FB-MMC)at the onshore station and the input and output characteristics of the diode rectifier at the offshore.Considering the characteristics of operation stability and decoupling between reactive power and active power,a simplified design based on double-loop droop control for offshore AC voltage is proposed after power flow and voltage–current(I–V)characteristics of the offshore wind farm being analyzed.Furthermore,the impact of onshore AC fault to offshore wind farm is analyzed,and a fast fault detection and protection strategy without relying on communication is proposed.Case studies carried out by PSCAD/EMTDC verify the effectiveness of the proposed control strategy for the start up,power fluctuation,and onshore and offshore fault conditions.
基金Project supported by the National Key R&D Program of China(No.2018AAA0101504)the Science and Technology Project of the State Grid Corporation of China:Fundamental Theory of Human in-the-Loop Hybrid-Augmented Intelligence for Power Grid Dispatch and Control。
文摘In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management,and control(CMC).We describe the historical development of complex system science and analyze the limitations of human intelligence and machine intelligence.The need for using human-machine HAI in complex systems is then explained in detail.The concept of“mutually trustworthy HM-KA”mechanism is proposed to tackle the CMC challenge,and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid dispatch.It is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.
基金Supported by National Key R&D Projects(Grant No.2018YFB0905500)National Natural Science Foundation of China(Grant No.51875498)+1 种基金Hebei Provincial Natural Science Foundation of China(Grant Nos.E2018203439,E2018203339,F2016203496)Key Scientific Research Projects Plan of Henan Higher Education Institutions(Grant No.19B460001)
文摘Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and timely. First, FCM clustering is employed to classify the data into different clusters, which helps to estimate whether there is a fault and how many fault types there are. If fault signals exist, the fault vibration signals are then demodulated and decomposed into different frequency bands by MMEMD in order to be analyzed further. In order to overcome the mode mixing defect of empirical mode decomposition (EMD), a novel method called MMEMD is proposed. It is an improvement to masking empirical mode decomposition (MEMD). By adding multi-masking signals to the signals to be decomposed in different levels, it can restrain low-frequency components from mixing in highfrequency components effectively in the sifting process and then suppress the mode mixing. It has the advantages of easy implementation and strong ability of suppressing modal mixing. The fault type is determined by Hilbert envelope finally. The results of simulation signal decomposition showed the high performance of MMEMD. Experiments of bearing fault diagnosis in wind turbine bearing fault diagnosis proved the validity and high accuracy of the new method.
基金This work was supported by the Major Science and Technology Project in Inner Mongolia Autonomous Region(2021ZD0040).
文摘Hydrogen production from renewable energy sources(RESs)is one of the effective ways to achieve carbon peak and carbon neutralization.In order to ensure the efficient,reliable and stable operation of the DC microgrid(MG)with an electric-hydrogen hybrid energy storage system(ESS),the operational constraints and static dynamic characteristics of a hydrogen energy storage system(HESS)needs to be fully considered.First,different hydrogen production systems,using water electrolysis are compared,and the modeling method of the electrolyzer is summarized.The operational control architecture of the DC MG with electric-hydrogen is analyzed.Combined with the working characteristics of the alkaline electrolyzer,the influence of hydrogen energy storage access on the operational mode of the DC MG is analyzed.The operational control strategies of the DC MG with electric-hydrogen hybrid ESS are classified and analyzed from four different aspects:static and dynamic characteristics of the hydrogen energy storage system,power distribution of the electric-hydrogen hybrid ESS and the efficiency optimization of hydrogen energy storage.Finally,the advantages of a modular hydrogen production system(HPS)are described,and the technical problems and research directions in the future are discussed.
基金Supported by National Natural Science Foundation of P. R. China (60572070, 60325311, 60534010) Natural Science Foundation of Liaoning Province (20022030)
文摘The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature. First, the so-called stochastic LaSalle theory is extended to some extent, and accordingly, the results of global ultimate boundedness for stochastic nonlinear systems are developed. Next, a new design scheme of fuzzy adaptive control is proposed. The advantage of it is that it does not require priori knowledge of virtual control gain function sign, which is usually demanded in many designs. At the same time, the track performance of closed-loop systems is improved by adaptive modifying the estimated error upper bound. By theoretical analysis, the signals of closed-loop systems are globally ultimately bounded in probability and the track error converges to a small residual set around the origin in 4th-power expectation.
基金financially supported in part by the National Key Research and Development Program of China under Grant 2020YFB1708400the National Natural Science Foundation of China(NSFC)under Grant 52120105008 and Grants 52005026。
文摘Digital twin is currently undergoing a significant transformation from the conceptual and theoretical research phase to the implementation and application phase.However,a universally adaptable research and development platform for digital twin is critically needed to meet the development requirements.Specifically,a publicly accessible simulation,testing,and validation platform which can support digital twin model building,data processing,algorithm design,configuration,etc.,is urgently required for researchers.Furthermore,for developers from the industry,a lowcode development platform that can offer a customizable suite of functions such as model creation,data management,protocol configuration,and visualization is urgently needed.Meanwhile,for enterprise users,there is a lack of an application management platform that can be configured and migrated for various application scenarios,functions,and modes.Therefore,based on the system research of digital twin theories and key technologies by the authors(such as the five-dimension digital twin model,digital twin modeling and digital twin data theory,digital twin standards,and so on),a digital twin software platform reference architecture,namely make Twin,is proposed and designed,as well as its ten core functions.The workflow of the make Twin and the interaction mechanisms among its core functions are described.Finally,a digital twin application system for a chemical fiber textile shop floor(CFTS)which was developed according to make Twin,is introduced,which validates the proposed reference architecture.
基金This work was supported by the Scientific Research Foundation of Harbin Institute of Technology project (HIT. MD. 2001.17).
文摘A set of system based on personal computer for the bi-directional reflectance distribution function (BRDF) measurement was developed, whose laser wavelengths cover 0.6328, 1.34, 3.39, and 10.6 μm from visible to infrared. Stray light in BRDF measurement system was analyzed. It can be reduced and suppressed by the design of the system light path in BRDF measurement system, the choice of the measuring scheme, the processing to the optoelectronic signal, and the radiation control of the optical components and mechanical equipments. So the minimum measurable value of BRDF is less than 10-5/sr.
基金financially supported by the National Natural Science Foundation of China (No. 51275020)the National Defense Pre-Research Foundation of China (No. 9140A18020212HK01210)
文摘NiCr–Cr3C2 metal–ceramic composite coating is commonly produced on metal substrate by laser cladding to be used as wear-resistant coating under medium- or high-temperature working conditions.The coating has high hardness, generally over three times that of the substrate.In order to make the hardness increase gradually from substrate to coating surface, the nickel-based alloy Ni45 was chosen as the transition layer and Ni Cr–Cr3C2 coating was indirectly cladded on 20Cr2Ni4 A substrate.Microstructure and composition of the coating were characterized by scanning electron microscope(SEM), energy-dispersive spectroscopy(EDS) and X-ray diffraction(XRD).Microhardness of the cross section of the coating was measured.Friction and wear behavior of Ni Cr–Cr3C2coating and substrate were investigated through sliding against the Si C ball at 20, 100 and 300 °C.The morphologies of worn surfaces were analyzed by SEM and EDS.The results show that the hardness of Ni45 transition layer is between that of the substrate and Ni Cr–Cr3C2coating, which avoids hardness jump and stress concentration of the coating.Ni Cr–Cr3C2coating contains hard phases of Cr3C2 and Cr7C3which enhance the wear resistance.With thetemperature increasing, friction coefficient and wear rate of the substrate increase significantly.Compared with the substrate, Ni Cr–Cr3C2coating has lower friction coefficient and wear rate at 100 and 300 °C, which verifies the good wear resistance of NiCr–Cr3C2 coating.
基金National Key Research and Development Program of China(2017YFA0700401)National Natural Science Foundation of China(81627805,81671726,81827808,81930048)+4 种基金Research Grants Council,University Grants Committee(25204416)Innovation and Technology Commission(GHP/043/19SZ,GHP/044/19GD,ITS/022/18)Guangdong Science and Technology Department(2019A1515011374,2019BT02X105)Science,Technology and Innovation Commission of Shenzhen Municipality(JCYJ20170818104421564)Youth Innovation Promotion Association of the Chinese Academy of Sciences(2018167)。
文摘Optical imaging through or inside scattering media, such as multimode fiber and biological tissues, has a significant impact in biomedicine yet is considered challenging due to the strong scattering nature of light. In the past decade, promising progress has been made in the field, largely benefiting from the invention of iterative optical wavefront shaping, with which deep-tissue high-resolution optical focusing and hence imaging becomes possible. Most of the reported iterative algorithms can overcome small perturbations on the noise level but fail to effectively adapt beyond the noise level, e.g., sudden strong perturbations. Reoptimizations are usually needed for significant decorrelation to the medium since these algorithms heavily rely on the optimization performance in the previous iterations. Such ineffectiveness is probably due to the absence of a metric that can gauge the deviation of the instant wavefront from the optimum compensation based on the concurrently measured optical focusing.In this study, a square rule of binary-amplitude modulation, directly relating the measured focusing performance with the error in the optimized wavefront, is theoretically proved and experimentally validated. With this simple rule, it is feasible to quantify how many pixels on the spatial light modulator incorrectly modulate the wavefront for the instant status of the medium or the whole system. As an example of application, we propose a novel algorithm, the dynamic mutation algorithm, which has high adaptability against perturbations by probing how far the optimization has gone toward the theoretically optimal performance. The diminished focus of scattered light can be effectively recovered when perturbations to the medium cause a significant drop in the focusing performance, which no existing algorithms can achieve due to their inherent strong dependence on previous optimizations. With further improvement, the square rule and the new algorithm may boost or inspire many applications, such as high-resolution optical imag
文摘Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is expected.With conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power systems.New analysis and control methods are needed for power systems to cope with the ongoing transformation.In the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power systems.Specifically,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.
基金supported by the Natural Science Foundation of Tianjin(No.14JCZDJC31900)
文摘A sliding mode control design for a miniature unmanned helicopter is presented. The control objective is to let the helicopter track some predefined velocity and yaw trajectories. A new sliding mode control design method is developed based on a linearized dynamic model. In order to facilitate the control design, the helicopter＇s dynamic model is divided into two subsystems,such as the longitudinal-lateral and the heading-heave subsystem. The proposed controller employs sliding mode control technique to compensate for the immeasurable flapping angles＇ dynamic effects and external disturbances. The global asymptotic stability（GAS） of the closed-loop system is proved by the Lyapunov based stability analysis. Numerical simulations demonstrate that the proposed controller can achieve superior tracking performance compared with the proportionalintegral-derivative（PID） and linear-quadratic regulator（LQR） cascaded controller in the presence of wind gust disturbances.
