Faults in traction system rectifiers can cause deterioration in system performance,robustness,and continuity.A single fault may propagate and cause the whole system to be shut down.Therefore,improving the robust stabi...Faults in traction system rectifiers can cause deterioration in system performance,robustness,and continuity.A single fault may propagate and cause the whole system to be shut down.Therefore,improving the robust stability and reliability of the control system is becoming more important.This study presents a robust current control based on a generalized internal model control(GIMC)for single-phase pulse width modulation(PWM)rectifier.The study aims to simultaneously achieve decent dynamic performance and robustness for the rectifiers under current sensor gain faults using generalized internal model control.H∞loop shaping can maintain robustness and achieve acceptable performance for the system in such cases.However,this controller will be conservative during an increase of sensor gain faults.That is,we sacrifice performance for robustness.Therefore,the GIMC structure is proposed to balance robustness and dynamic performance in such cases.The proposed control scheme during sensor gain faults is investigated.Furthermore,the robustness is analyzed using the v-gap metric.The proposed GIMC control framework consists of two parts,nominal and robustness controllers.The system is controlled solely by the nominal controller in normal operation in the absence of current sensor gain faults.If they occur,then the robustness controller will be active to maintain system robustness and achieve acceptable performance.The nominal controller is chosen as H∞loop shaping to assure nominal performance,while the robustness controller is chosen as the plant inverse cascaded by low pass filter to compensate for the sensor gain faults.Hardware-in-loop experimental results indicate that the suggested fault-tolerant control achieves good performance and robustness in comparison to the H∞loop shaping controller.展开更多
Water resources are precious in arid and semi-arid areas such as the Wadis of Iran. To sustainably manage these limited water resources, the residents of the Iranian Wadis have been traditionally using several water u...Water resources are precious in arid and semi-arid areas such as the Wadis of Iran. To sustainably manage these limited water resources, the residents of the Iranian Wadis have been traditionally using several water use systems(WUSs) which affect natural hydrological processes. In this study, WUSs and soil and water conservation measures(SWCMs) were integrated in a hydrological model of the Halilrood Basin in Iran. The Soil and Water Assessment Tool(SWAT) model was used to simulate the hydrological processes between 1993 and 2009 at daily time scale. To assess the importance of WUSs and SWCMs, we compared a model setup without WUSs and SWCMs(Default model) with a model setup with WUSs and SWCMs(WUS-SWCM model). When compared to the observed daily stream flow, the number of acceptable calibration runs as defined by the performance thresholds(Nash-Sutcliffe efficiency(NSE)≥0.68, –25%≤percent bias(PBIAS)≤25% and ratio of standard deviation(RSR)≤0.56) is 177 for the Default model and 1945 for the WUS-SWCM model. Also, the average Kling–Gupta efficiency(KGE) of acceptable calibration runs for the WUS-SWCM model is higher in both calibration and validation periods. When WUSs and SWCMs are implemented, surface runoff(between 30% and 99%) and water yield(between 0 and 18%) decreased in all sub-basins. Moreover, SWCMs lead to a higher contribution of groundwater flow to the channel and compensate for the extracted water by WUSs from the shallow aquifer. In summary, implementing WUSs and SWCMs in the SWAT model enhances model plausibility significantly.展开更多
Existing systems use key performance indicators(KPIs)as metrics for physical layer(PHY)optimization,which suffers from the problem of overoptimization,because some unnecessary PHY enhancements are imperceptible to ter...Existing systems use key performance indicators(KPIs)as metrics for physical layer(PHY)optimization,which suffers from the problem of overoptimization,because some unnecessary PHY enhancements are imperceptible to terminal users and thus induce additional cost and energy waste.Therefore,it is necessary to utilize directly the quality of experience(QoE)of user as a metric of optimization,which can achieve the global optimum of QoE under cost and energy constraints.However,QoE is still a metric of application layer that cannot be easily used to design and optimize the PHY.To address this problem,we in this paper propose a novel end-to-end QoE(E2E-QoE)based optimization architecture at the user-side for the first time.Specifically,a cross-layer parameterized model is proposed to establish the relationship between PHY and E2E-QoE.Based on this,an E2E-QoE oriented PHY anomaly diagnosis method is further designed to locate the time and root cause of anomalies.Finally,we investigate to optimize the PHY algorithm directly based on the E2E-QoE.The proposed frameworks and algorithms are all validated using the data from real fifth-generation(5G)mobile system,which show that using E2E-QoE as the metric of PHY optimization is feasible and can outperform existing schemes.展开更多
We address the problem of metric learning for multi-view data. Many metric learning algorithms have been proposed, most of them focus just on single view circumstances, and only a few deal with multi-view data. In thi...We address the problem of metric learning for multi-view data. Many metric learning algorithms have been proposed, most of them focus just on single view circumstances, and only a few deal with multi-view data. In this paper, motivated by the co-training framework, we propose an algorithm-independent framework, named co-metric, to learn Mahalanobis metrics in multi-view settings. In its implementation, an off-the-shelf single-view metric learning algorithm is used to learn metrics in individual views of a few labeled examples. Then the most confidently-labeled examples chosen from the unlabeled set are used to guide the metric learning in the next loop. This procedure is repeated until some stop criteria are met. The framework can accommodate most existing metric learning algorithms whether types-of- side-information or example-labels are used. In addition it can naturally deal with semi-supervised circumstances under more than two views. Our comparative experiments demon- strate its competiveness and effectiveness.展开更多
Based on a generalized Yang-Mills framework, gravitational and strong interactions can be unified in analogy with the unification in the electroweak theory. By gauging T （4） × [SU （3）] color in flat space-tim...Based on a generalized Yang-Mills framework, gravitational and strong interactions can be unified in analogy with the unification in the electroweak theory. By gauging T （4） × [SU （3）] color in flat space-time, we have a unified model of chromo-gravity with a new tensor gauge field, which couples universally to all gluons, quarks and anti-quarks. The space-time translational gauge symmetry assures that all wave equations of quarks and gluons reduce to a Hamilton-Jacobi equation with the same ‘effective Riemann metric tensors’ in the geometric-optics （or classical） limit. The emergence of ef f ective metric tensors in the classical limit is essential for the unified model to agree with experiments. The unified model suggests that all gravitational, strong and electroweak interactions appear to be dictated by gauge symmetries in the generalized Yang-Mills framework.展开更多
基金supported by the National Natural Science Foundation of China(No.61733015)High-Speed Railway Joint Funds of the National Science Foundation of China(No.U1934204).
文摘Faults in traction system rectifiers can cause deterioration in system performance,robustness,and continuity.A single fault may propagate and cause the whole system to be shut down.Therefore,improving the robust stability and reliability of the control system is becoming more important.This study presents a robust current control based on a generalized internal model control(GIMC)for single-phase pulse width modulation(PWM)rectifier.The study aims to simultaneously achieve decent dynamic performance and robustness for the rectifiers under current sensor gain faults using generalized internal model control.H∞loop shaping can maintain robustness and achieve acceptable performance for the system in such cases.However,this controller will be conservative during an increase of sensor gain faults.That is,we sacrifice performance for robustness.Therefore,the GIMC structure is proposed to balance robustness and dynamic performance in such cases.The proposed control scheme during sensor gain faults is investigated.Furthermore,the robustness is analyzed using the v-gap metric.The proposed GIMC control framework consists of two parts,nominal and robustness controllers.The system is controlled solely by the nominal controller in normal operation in the absence of current sensor gain faults.If they occur,then the robustness controller will be active to maintain system robustness and achieve acceptable performance.The nominal controller is chosen as H∞loop shaping to assure nominal performance,while the robustness controller is chosen as the plant inverse cascaded by low pass filter to compensate for the sensor gain faults.Hardware-in-loop experimental results indicate that the suggested fault-tolerant control achieves good performance and robustness in comparison to the H∞loop shaping controller.
基金The German Academic Exchange Service (DAAD) provided funding for the first authorThe German Federal Ministry of Education and Research (BMBF) provided funding for the second author through the “GLANCE” project (Global Change Effects on River Ecosystems, 01LN1320A)。
文摘Water resources are precious in arid and semi-arid areas such as the Wadis of Iran. To sustainably manage these limited water resources, the residents of the Iranian Wadis have been traditionally using several water use systems(WUSs) which affect natural hydrological processes. In this study, WUSs and soil and water conservation measures(SWCMs) were integrated in a hydrological model of the Halilrood Basin in Iran. The Soil and Water Assessment Tool(SWAT) model was used to simulate the hydrological processes between 1993 and 2009 at daily time scale. To assess the importance of WUSs and SWCMs, we compared a model setup without WUSs and SWCMs(Default model) with a model setup with WUSs and SWCMs(WUS-SWCM model). When compared to the observed daily stream flow, the number of acceptable calibration runs as defined by the performance thresholds(Nash-Sutcliffe efficiency(NSE)≥0.68, –25%≤percent bias(PBIAS)≤25% and ratio of standard deviation(RSR)≤0.56) is 177 for the Default model and 1945 for the WUS-SWCM model. Also, the average Kling–Gupta efficiency(KGE) of acceptable calibration runs for the WUS-SWCM model is higher in both calibration and validation periods. When WUSs and SWCMs are implemented, surface runoff(between 30% and 99%) and water yield(between 0 and 18%) decreased in all sub-basins. Moreover, SWCMs lead to a higher contribution of groundwater flow to the channel and compensate for the extracted water by WUSs from the shallow aquifer. In summary, implementing WUSs and SWCMs in the SWAT model enhances model plausibility significantly.
文摘Existing systems use key performance indicators(KPIs)as metrics for physical layer(PHY)optimization,which suffers from the problem of overoptimization,because some unnecessary PHY enhancements are imperceptible to terminal users and thus induce additional cost and energy waste.Therefore,it is necessary to utilize directly the quality of experience(QoE)of user as a metric of optimization,which can achieve the global optimum of QoE under cost and energy constraints.However,QoE is still a metric of application layer that cannot be easily used to design and optimize the PHY.To address this problem,we in this paper propose a novel end-to-end QoE(E2E-QoE)based optimization architecture at the user-side for the first time.Specifically,a cross-layer parameterized model is proposed to establish the relationship between PHY and E2E-QoE.Based on this,an E2E-QoE oriented PHY anomaly diagnosis method is further designed to locate the time and root cause of anomalies.Finally,we investigate to optimize the PHY algorithm directly based on the E2E-QoE.The proposed frameworks and algorithms are all validated using the data from real fifth-generation(5G)mobile system,which show that using E2E-QoE as the metric of PHY optimization is feasible and can outperform existing schemes.
基金We would like to thank the National Natural Science Foundations of China （NSFC） （Grant Nos. 61035003 and 61170151） for support.
文摘We address the problem of metric learning for multi-view data. Many metric learning algorithms have been proposed, most of them focus just on single view circumstances, and only a few deal with multi-view data. In this paper, motivated by the co-training framework, we propose an algorithm-independent framework, named co-metric, to learn Mahalanobis metrics in multi-view settings. In its implementation, an off-the-shelf single-view metric learning algorithm is used to learn metrics in individual views of a few labeled examples. Then the most confidently-labeled examples chosen from the unlabeled set are used to guide the metric learning in the next loop. This procedure is repeated until some stop criteria are met. The framework can accommodate most existing metric learning algorithms whether types-of- side-information or example-labels are used. In addition it can naturally deal with semi-supervised circumstances under more than two views. Our comparative experiments demon- strate its competiveness and effectiveness.
基金Supported by Jing Shin Research Fund of UMassD Foundation
文摘Based on a generalized Yang-Mills framework, gravitational and strong interactions can be unified in analogy with the unification in the electroweak theory. By gauging T （4） × [SU （3）] color in flat space-time, we have a unified model of chromo-gravity with a new tensor gauge field, which couples universally to all gluons, quarks and anti-quarks. The space-time translational gauge symmetry assures that all wave equations of quarks and gluons reduce to a Hamilton-Jacobi equation with the same ‘effective Riemann metric tensors’ in the geometric-optics （or classical） limit. The emergence of ef f ective metric tensors in the classical limit is essential for the unified model to agree with experiments. The unified model suggests that all gravitational, strong and electroweak interactions appear to be dictated by gauge symmetries in the generalized Yang-Mills framework.
