The characteristic modeling problem of flight vehicles'attitude dynamics is considered in this paper.In terms of the affine nonlinear system with triangle form of flight vehicles'attitude dynamics,a general me...The characteristic modeling problem of flight vehicles'attitude dynamics is considered in this paper.In terms of the affine nonlinear system with triangle form of flight vehicles'attitude dynamics,a general method is presented to compress the dynamics into the characteristic model parameters,by introducing the time scale of nonlinear systems and a class of system states related compress functions.The parameter region and limit of the characteristic model are also given.From the given parameter region it is seen that the bound of the characteristic model parameters is dependent on the sampling period,the modeling error,the system order and the system change rate.The modeling error of the established characteristic model can be arbitrarily small according to the control precision,showing the difference between the characteristic model and other model reduction methods,that is,no system information is lost using this approach.On the basis of this modeling approach,the characteristic model of the flexible satellite attitude is established,as well as the bound and limit of the parameters,which sets a theoretical foundation for characteristic model based control design of flight vehicles.展开更多
This study investigated the regime-dependent predictability using convective-scale ensemble forecasts initialized with different initial condition perturbations in the Yangtze and Huai River basin(YHRB)of East China.T...This study investigated the regime-dependent predictability using convective-scale ensemble forecasts initialized with different initial condition perturbations in the Yangtze and Huai River basin(YHRB)of East China.The scale-dependent error growth(ensemble variability)and associated impact on precipitation forecasts(precipitation uncertainties)were quantitatively explored for 13 warm-season convective events that were categorized in terms of strong forcing and weak forcing.The forecast error growth in the strong-forcing regime shows a stepwise increase with increasing spatial scale,while the error growth shows a larger temporal variability with an afternoon peak appearing at smaller scales under weak forcing.This leads to the dissimilarity of precipitation uncertainty and shows a strong correlation between error growth and precipitation across spatial scales.The lateral boundary condition errors exert a quasi-linear increase on error growth with time at the larger scale,suggesting that the large-scale flow could govern the magnitude of error growth and associated precipitation uncertainties,especially for the strong-forcing regime.Further comparisons between scale-based initial error sensitivity experiments show evident scale interaction including upscale transfer of small-scale errors and downscale cascade of larger-scale errors.Specifically,small-scale errors are found to be more sensitive in the weak-forcing regime than those under strong forcing.Meanwhile,larger-scale initial errors are responsible for the error growth after 4 h and produce the precipitation uncertainties at the meso-β-scale.Consequently,these results can be used to explain underdispersion issues in convective-scale ensemble forecasts and provide feedback for ensemble design over the YHRB.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.60736023,60704014)
文摘The characteristic modeling problem of flight vehicles'attitude dynamics is considered in this paper.In terms of the affine nonlinear system with triangle form of flight vehicles'attitude dynamics,a general method is presented to compress the dynamics into the characteristic model parameters,by introducing the time scale of nonlinear systems and a class of system states related compress functions.The parameter region and limit of the characteristic model are also given.From the given parameter region it is seen that the bound of the characteristic model parameters is dependent on the sampling period,the modeling error,the system order and the system change rate.The modeling error of the established characteristic model can be arbitrarily small according to the control precision,showing the difference between the characteristic model and other model reduction methods,that is,no system information is lost using this approach.On the basis of this modeling approach,the characteristic model of the flexible satellite attitude is established,as well as the bound and limit of the parameters,which sets a theoretical foundation for characteristic model based control design of flight vehicles.
基金supported by the National Key Research and Development Program of China(Grant No.2017YFC1502103)the National Natural Science Foundation of China(Grant Nos.41430427 and 41705035)+1 种基金the China Scholarship Councilthe Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX17_0876)。
文摘This study investigated the regime-dependent predictability using convective-scale ensemble forecasts initialized with different initial condition perturbations in the Yangtze and Huai River basin(YHRB)of East China.The scale-dependent error growth(ensemble variability)and associated impact on precipitation forecasts(precipitation uncertainties)were quantitatively explored for 13 warm-season convective events that were categorized in terms of strong forcing and weak forcing.The forecast error growth in the strong-forcing regime shows a stepwise increase with increasing spatial scale,while the error growth shows a larger temporal variability with an afternoon peak appearing at smaller scales under weak forcing.This leads to the dissimilarity of precipitation uncertainty and shows a strong correlation between error growth and precipitation across spatial scales.The lateral boundary condition errors exert a quasi-linear increase on error growth with time at the larger scale,suggesting that the large-scale flow could govern the magnitude of error growth and associated precipitation uncertainties,especially for the strong-forcing regime.Further comparisons between scale-based initial error sensitivity experiments show evident scale interaction including upscale transfer of small-scale errors and downscale cascade of larger-scale errors.Specifically,small-scale errors are found to be more sensitive in the weak-forcing regime than those under strong forcing.Meanwhile,larger-scale initial errors are responsible for the error growth after 4 h and produce the precipitation uncertainties at the meso-β-scale.Consequently,these results can be used to explain underdispersion issues in convective-scale ensemble forecasts and provide feedback for ensemble design over the YHRB.
