This paper aims to investigate the critical stability of a multi-degree-of-freedom(multi-DOF)real-time hybrid simulation(RTHS).First,the critical time-delay analysis models are developed using the continuous-and discr...This paper aims to investigate the critical stability of a multi-degree-of-freedom(multi-DOF)real-time hybrid simulation(RTHS).First,the critical time-delay analysis models are developed using the continuous-and discrete-time root locus(RL)techniques,respectively.A bilinear transform is introduced into the first-order Padéapproximation while conducting the discrete RL analysis.Based on this technique,the time delay can be explicitly used as the gain factor and thus the instability mechanism of the multi-DOF RTHS system can be analyzed.Subsequently,the critical time delays calculated by the continuous-and discrete-time RL techniques,respectively,are compared for a 2-DOF RTHS system.It is shown that assuming the RTHS system to be a continuous-time system will result in overestimating the critical time delay.Finally,theoretically calculated critical delays are demonstrated and validated by numerical simulation and a set of RTHS experiments.Parametric analysis provides a glimpse of the effects of time step,frequency and damping ratio in a performing partitioning scheme.The constructed analysis model proves to be useful for evaluating the critical time delay to predict stability and performance,therefore facilitating successful RTHS.展开更多
A new semi-serial fusion method of multiple feature based on learning using privileged information(LUPI) model was put forward.The exploitation of LUPI paradigm permits the improvement of the learning accuracy and its...A new semi-serial fusion method of multiple feature based on learning using privileged information(LUPI) model was put forward.The exploitation of LUPI paradigm permits the improvement of the learning accuracy and its stability,by additional information and computations using optimization methods.The execution time is also reduced,by sparsity and dimension of testing feature.The essence of improvements obtained using multiple features types for the emotion recognition(speech expression recognition),is particularly applicable when there is only one modality but still need to improve the recognition.The results show that the LUPI in unimodal case is effective when the size of the feature is considerable.In comparison to other methods using one type of features or combining them in a concatenated way,this new method outperforms others in recognition accuracy,execution reduction,and stability.展开更多
基金National Natural Science Foundation of China under Grant Nos.51725901 and 51639006。
文摘This paper aims to investigate the critical stability of a multi-degree-of-freedom(multi-DOF)real-time hybrid simulation(RTHS).First,the critical time-delay analysis models are developed using the continuous-and discrete-time root locus(RL)techniques,respectively.A bilinear transform is introduced into the first-order Padéapproximation while conducting the discrete RL analysis.Based on this technique,the time delay can be explicitly used as the gain factor and thus the instability mechanism of the multi-DOF RTHS system can be analyzed.Subsequently,the critical time delays calculated by the continuous-and discrete-time RL techniques,respectively,are compared for a 2-DOF RTHS system.It is shown that assuming the RTHS system to be a continuous-time system will result in overestimating the critical time delay.Finally,theoretically calculated critical delays are demonstrated and validated by numerical simulation and a set of RTHS experiments.Parametric analysis provides a glimpse of the effects of time step,frequency and damping ratio in a performing partitioning scheme.The constructed analysis model proves to be useful for evaluating the critical time delay to predict stability and performance,therefore facilitating successful RTHS.
基金supported by the National Key Research and Development Program of China(2016YFB1001404)the National Natural Science Foundation of China(61873299,61702036,61572075)
文摘A new semi-serial fusion method of multiple feature based on learning using privileged information(LUPI) model was put forward.The exploitation of LUPI paradigm permits the improvement of the learning accuracy and its stability,by additional information and computations using optimization methods.The execution time is also reduced,by sparsity and dimension of testing feature.The essence of improvements obtained using multiple features types for the emotion recognition(speech expression recognition),is particularly applicable when there is only one modality but still need to improve the recognition.The results show that the LUPI in unimodal case is effective when the size of the feature is considerable.In comparison to other methods using one type of features or combining them in a concatenated way,this new method outperforms others in recognition accuracy,execution reduction,and stability.
