This paper addresses the problem of creating a geometric map with a mobile robot in a dynamic indoor environment.To form an accurate model of the environment,we present a novel map representation called the'grid v...This paper addresses the problem of creating a geometric map with a mobile robot in a dynamic indoor environment.To form an accurate model of the environment,we present a novel map representation called the'grid vector',which combines each vector that represents a directed line segment with a slender occupancy grid map.A modified expectation maximization(EM)based approach is proposed to evaluate the dynamic objects and simultaneously estimate the robot path and the map of the environment.The probability of each grid vector is evaluated in the expectation step and then used to distinguish the vector into static and dynamic ones.The robot path and map are estimated in the maximization step with a graph-based simultaneous localization and mapping(SLAM)method.The representation we introduce provides advantages on making the SLAM method strictly statistic,reducing memory cost,identifying the dynamic objects,and improving the accuracy of the data associations.The SLAM algorithm we present is efficient in computation and convergence.Experiments on three different kinds of data sets show that our representation and algorithm can generate an accurate static map in a dynamic indoor environment.展开更多
By making use of Thiele-type bivariate branched continued fractions and Sumelson inverse,we construct a few kinds of bivariate vector valued rational interpolonts (BVRIs) over rectangular grids and find out certain re...By making use of Thiele-type bivariate branched continued fractions and Sumelson inverse,we construct a few kinds of bivariate vector valued rational interpolonts (BVRIs) over rectangular grids and find out certain relations among these BVRIs such as boundary identity and duality.展开更多
In wind power generation system the grid-connected inverter is an important section for energy conversion and transmission, of which the performance has a direct influence on the entire wind power generation system. T...In wind power generation system the grid-connected inverter is an important section for energy conversion and transmission, of which the performance has a direct influence on the entire wind power generation system. The mathematical model of the grid-connected inverter is deduced firstly. Then, the space vector pulse width modulation （SVPWM） is analyzed. The power factor can be controlled close to unity, leading or lagging, which is realized based on H-type current controller and grid voltage vector-oriented control. The control strategy is verified by the simulation and experimental results with a good sinusoidal current, a small harmonic component and a fast dynamic response.展开更多
Online fault detection is one of the key technologies to improve the performance of cloud systems. The current data of cloud systems is to be monitored, collected and used to reflect their state. Its use can potential...Online fault detection is one of the key technologies to improve the performance of cloud systems. The current data of cloud systems is to be monitored, collected and used to reflect their state. Its use can potentially help cloud managers take some timely measures before fault occurrence in clouds. Because of the complex structure and dynamic change characteristics of the clouds, existing fault detection methods suffer from the problems of low efficiency and low accuracy. In order to solve them, this work proposes an online detection model based on asystematic parameter-search method called SVM-Grid, whose construction is based on a support vector machine(SVM). SVM-Grid is used to optimize parameters in SVM. Proper attributes of a cloud system's running data are selected by using Pearson correlation and principal component analysis for the model. Strategies of predicting cloud faults and updating fault sample databases are proposed to optimize the model and improve its performance.In comparison with some representative existing methods, the proposed model can achieve more efficient and accurate fault detection for cloud systems.展开更多
基金supported by the National Natural Science Foundation of China(Nos.60675049 and 61075078)the National High-Tech Research and Development Program(863)of China(No.2008AA04Z209)
文摘This paper addresses the problem of creating a geometric map with a mobile robot in a dynamic indoor environment.To form an accurate model of the environment,we present a novel map representation called the'grid vector',which combines each vector that represents a directed line segment with a slender occupancy grid map.A modified expectation maximization(EM)based approach is proposed to evaluate the dynamic objects and simultaneously estimate the robot path and the map of the environment.The probability of each grid vector is evaluated in the expectation step and then used to distinguish the vector into static and dynamic ones.The robot path and map are estimated in the maximization step with a graph-based simultaneous localization and mapping(SLAM)method.The representation we introduce provides advantages on making the SLAM method strictly statistic,reducing memory cost,identifying the dynamic objects,and improving the accuracy of the data associations.The SLAM algorithm we present is efficient in computation and convergence.Experiments on three different kinds of data sets show that our representation and algorithm can generate an accurate static map in a dynamic indoor environment.
基金Supported by National Natural Science Foundation Of China （60873235, 60473099）, Science-Technology Development Key Project of Jilin Province of China （20080318）, and Program of New Century Excellent Talents in University of China （NCET-06-0300）
基金Supported by the National Natural Science Foundation of China.
文摘By making use of Thiele-type bivariate branched continued fractions and Sumelson inverse,we construct a few kinds of bivariate vector valued rational interpolonts (BVRIs) over rectangular grids and find out certain relations among these BVRIs such as boundary identity and duality.
基金supported by Delta Power Electronic Science and Education Development in 2007 (Grant No.DRES2007002)
文摘In wind power generation system the grid-connected inverter is an important section for energy conversion and transmission, of which the performance has a direct influence on the entire wind power generation system. The mathematical model of the grid-connected inverter is deduced firstly. Then, the space vector pulse width modulation （SVPWM） is analyzed. The power factor can be controlled close to unity, leading or lagging, which is realized based on H-type current controller and grid voltage vector-oriented control. The control strategy is verified by the simulation and experimental results with a good sinusoidal current, a small harmonic component and a fast dynamic response.
基金supported by the National Natural Science Foundation of China(61472005,61201252)CERNET Innovation Project(NGII20160207)
文摘Online fault detection is one of the key technologies to improve the performance of cloud systems. The current data of cloud systems is to be monitored, collected and used to reflect their state. Its use can potentially help cloud managers take some timely measures before fault occurrence in clouds. Because of the complex structure and dynamic change characteristics of the clouds, existing fault detection methods suffer from the problems of low efficiency and low accuracy. In order to solve them, this work proposes an online detection model based on asystematic parameter-search method called SVM-Grid, whose construction is based on a support vector machine(SVM). SVM-Grid is used to optimize parameters in SVM. Proper attributes of a cloud system's running data are selected by using Pearson correlation and principal component analysis for the model. Strategies of predicting cloud faults and updating fault sample databases are proposed to optimize the model and improve its performance.In comparison with some representative existing methods, the proposed model can achieve more efficient and accurate fault detection for cloud systems.
