动态电压恢复器(dynamic voltage restorer,DVR)的响应速度是衡量DVR特性的重要指标,锁相环和电压跌落检测算法则是决定其响应速度的2个关键因素,而电网电压畸变、跌落过程中发生的相位跳变和电压不平衡制约着锁相环和检测算法的快速性...动态电压恢复器(dynamic voltage restorer,DVR)的响应速度是衡量DVR特性的重要指标,锁相环和电压跌落检测算法则是决定其响应速度的2个关键因素,而电网电压畸变、跌落过程中发生的相位跳变和电压不平衡制约着锁相环和检测算法的快速性。该文结合最小方差(least error squares,LES)滤波器和改进对称分量法设计了新的软件锁相环和电压跌落检测算法,对这2种方法进行详细的理论推导,阐明各频次的正负序分量解耦的机理。在Matlab/Simulink中搭建仿真模型,与传统锁相环方法和电压跌落检测算法进行对比分析。最后,在电压跌落平台进行工业样机验证,结果表明所提方法可行有效,且具有较高的响应速度。展开更多
According to the biased angles provided by the bistatic sensors, the necessary condition of observability and Cramer-Rao low bounds for the bistatic system are derived and analyzed, respectively. Additionally, a dual ...According to the biased angles provided by the bistatic sensors, the necessary condition of observability and Cramer-Rao low bounds for the bistatic system are derived and analyzed, respectively. Additionally, a dual Kalman filter method is presented with the purpose of eliminating the effect of biased angles on the state variable estimation. Finally, Monte-Carlo simulations are conducted in the observable scenario. Simulation results show that the proposed theory holds true, and the dual Kalman filter method can estimate state variable and biased angles simultaneously. Furthermore, the estimated results can achieve their Cramer-Rao tow bounds.展开更多
A hybrid grid-point statistical interpolation-ensemble transform Kalman filter (GSI-ETKF) data assimilation system for the Weather Research and Forecasting (WRF) model was developed and applied to typhoon track foreca...A hybrid grid-point statistical interpolation-ensemble transform Kalman filter (GSI-ETKF) data assimilation system for the Weather Research and Forecasting (WRF) model was developed and applied to typhoon track forecast with simulated dropsonde observations. This hybrid system showed significantly improved results with respect to tropical cyclone track forecast compared to the standard GSI system in the case of Muifa in 2011. Further analyses revealed that the flow-dependent ensemble covariance was the major contributor to the better performance of the GSI-ETKF system than the standard GSI system; the GSI-ETKF system was found to be potentially able to adjust the position of the typhoon vortex systematically and better update the environmental field.展开更多
Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Fir...Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Firstly, combined with the residual detection strategy, effective observations are cor- rectly identified. Secondly, according to the missing characteristic of observations and the structural feature of unscented Kalman filter, the iterative process of the single-sensor unscented Kalman filter in intermittent observations is given. The key idea is that the state estimation and its error covariance matrix are replaced by the state one-step prediction and its error covariance matrix, when the phe- nomenon of observations missing occurs. Finally, based on the realization mechanism of federated filter, a new fusion framework of state estimation from each local node is designed. And the filtering precision of system state is improved further by the effective management of observations missing and the rational utilization of redundancy and complementary information among multi-sensor observa- tions. The theory analysis and simulation results show the feasibility and effectiveness of the pro- posed algorithm.展开更多
文摘动态电压恢复器(dynamic voltage restorer,DVR)的响应速度是衡量DVR特性的重要指标,锁相环和电压跌落检测算法则是决定其响应速度的2个关键因素,而电网电压畸变、跌落过程中发生的相位跳变和电压不平衡制约着锁相环和检测算法的快速性。该文结合最小方差(least error squares,LES)滤波器和改进对称分量法设计了新的软件锁相环和电压跌落检测算法,对这2种方法进行详细的理论推导,阐明各频次的正负序分量解耦的机理。在Matlab/Simulink中搭建仿真模型,与传统锁相环方法和电压跌落检测算法进行对比分析。最后,在电压跌落平台进行工业样机验证,结果表明所提方法可行有效,且具有较高的响应速度。
基金the Natural Science Foundation of Jiangsu Province, China (BK2004132).
文摘According to the biased angles provided by the bistatic sensors, the necessary condition of observability and Cramer-Rao low bounds for the bistatic system are derived and analyzed, respectively. Additionally, a dual Kalman filter method is presented with the purpose of eliminating the effect of biased angles on the state variable estimation. Finally, Monte-Carlo simulations are conducted in the observable scenario. Simulation results show that the proposed theory holds true, and the dual Kalman filter method can estimate state variable and biased angles simultaneously. Furthermore, the estimated results can achieve their Cramer-Rao tow bounds.
基金supported by the Project for public welfare (Meteorology) of China(Grant No.GYHY201206006)the National Natural Science Foundation of China(Grant Nos.40975067 and 41175094)
文摘A hybrid grid-point statistical interpolation-ensemble transform Kalman filter (GSI-ETKF) data assimilation system for the Weather Research and Forecasting (WRF) model was developed and applied to typhoon track forecast with simulated dropsonde observations. This hybrid system showed significantly improved results with respect to tropical cyclone track forecast compared to the standard GSI system in the case of Muifa in 2011. Further analyses revealed that the flow-dependent ensemble covariance was the major contributor to the better performance of the GSI-ETKF system than the standard GSI system; the GSI-ETKF system was found to be potentially able to adjust the position of the typhoon vortex systematically and better update the environmental field.
基金Supported by the National Natural Science Foundation(NNSF)of China under Grant(No.61300214)the Science and Technology Innovation Team Support Plan of Education Department of Henan Province(No.13IRTSTHN021)+5 种基金the Science and Technology Research Key Project of Education Department of Henan Province(No.13A413066)the Basic and Frontier Technology Research Plan of Henan Province(No.132300410148)the Funding Scheme of Young Key Teacher of Henan Province Universities(No.2013GGJS-026)the Key Project of Teaching Reform Research of Henan University(No.HDXJJG2013-07)the Postdoctoral Science Fund of Henan Province(No.2013029)the Postdoctoral Science Fund of China(No.2014M551999)
文摘Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Firstly, combined with the residual detection strategy, effective observations are cor- rectly identified. Secondly, according to the missing characteristic of observations and the structural feature of unscented Kalman filter, the iterative process of the single-sensor unscented Kalman filter in intermittent observations is given. The key idea is that the state estimation and its error covariance matrix are replaced by the state one-step prediction and its error covariance matrix, when the phe- nomenon of observations missing occurs. Finally, based on the realization mechanism of federated filter, a new fusion framework of state estimation from each local node is designed. And the filtering precision of system state is improved further by the effective management of observations missing and the rational utilization of redundancy and complementary information among multi-sensor observa- tions. The theory analysis and simulation results show the feasibility and effectiveness of the pro- posed algorithm.
