In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained f...In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.展开更多
The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy...The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy and limited application range,the use of TNT equivalence for predicting explosion parameters in a confined space is rare.Compared with explosions in free fields,the process of explosive energy release in a confined space is closely related to various factors such as oxygen balance,combustible components content,and surrounding oxygen content.Studies have shown that in a confined space,negative oxygen balance explosives react with surrounding oxygen during afterburning,resulting in additional energy release and enhanced blast effects.The mechanism of energy release during afterburning is highly complex,making it challenging to determine the TNT equivalence for blast effects in a confined space.Therefore,this remains an active area of research.In this study,internal blast experiments were conducted using TNT and three other explosives under both air and N_2(Nitrogen)conditions to obtain explosion parameters including blast wave overpressure,quasi-static pressure,and temperature.The influences of oxygen balance and external oxygen content on energy release are analyzed.The author proposes principles for determining TNT equivalence for internal explosions while verifying the accuracy of obtained blast parameters through calculations based on TNT equivalence.These findings can serve as references for predicting blast performance.展开更多
The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncerta...This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.展开更多
To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on th...To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on the target detection performance,firstly,a spatial detection model of distributed high-frequency surface wave radar(distributed-HFSWR)is established in this paper.In this model,a method for accurate extraction of direct wave spectrum based on curve fitting is proposed to obtain accurate system internal delay and frequency synchronization error under complex electromagnetic environment background and low signal to noise ratio(SNR),and to compensate for the shift of range and Doppler frequency caused by time-frequency synchronization error.The direct wave component is extracted from the spectrum,the range estimation error and Doppler estimation error are reduced by the method of curve fitting,and the fitting accuracy of the parameters is improved.Then,the influence of frequency synchronization error on target range and radial Doppler velocity is quantitatively analyzed.The relationship between frequency synchronization error and radial Doppler velocity shift and range shift is given.Finally,the system synchronization parameters of the trial distributed-HFSWR are obtained by the proposed spectrum extraction method based on curve fitting,the experimental data is compensated to correct the shift of the target,and finally the correct target parameter information is obtained.Simulations and experimental results demonstrate the superiority and correctness of the proposed method,theoretical derivation and detection model proposed in this paper.展开更多
In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LST...In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LSTM) neural network is nested into the extended Kalman filter(EKF) to modify the Kalman gain such that the filtering performance is improved in the presence of large model uncertainties. To avoid the unstable network output caused by the abrupt changes of system states,an adaptive correction factor is introduced to correct the network output online. In the process of training the network, a multi-gradient descent learning mode is proposed to better fit the internal state of the system, and a rolling training is used to implement an online prediction logic. Based on the Lyapunov second method, we discuss the stability of the system, the result shows that when the training error of neural network is sufficiently small, the system is asymptotically stable. With its application to the estimation of time-varying parameters of a missile dual control system, the LSTM-EKF shows better filtering performance than the EKF and adaptive EKF(AEKF) when there exist large uncertainties in the system model.展开更多
为研究农业机械与水田壤土间的相互作用,需获取水田壤土的物理及接触参数。结合物理堆积试验,以休止角作为响应值,采用离散元法(DEM)并选取Hertz-Mindlin with JKR(Johnson-Kendall-Roberts)接触模型对长江中游地区水田壤土展开参数标...为研究农业机械与水田壤土间的相互作用,需获取水田壤土的物理及接触参数。结合物理堆积试验,以休止角作为响应值,采用离散元法(DEM)并选取Hertz-Mindlin with JKR(Johnson-Kendall-Roberts)接触模型对长江中游地区水田壤土展开参数标定研究。首先,通过物理堆积试验获取了壤土休止角(AoR)与含水率间的定量关系,由不同含水率土壤的堆积结果筛分出4种代表性堆积形态,由于水田壤土堆积体轮廓外形比较独特,因此仅对其左右两侧轮廓采用三次多项式进行局部拟合,计算其休止角。以长江中游地区水田壤土成因和预试验为依据来确定其离散元模型中9个参数的高低水平值,通过Plackett-Burman试验设计进行方差分析,发现壤土剪切模量、壤土间动摩擦因数、壤土与不锈钢间静摩擦因数和JKR表面能对AoR影响明显。然后,采用基于响应面法(RSM)原理的Box-Behnken试验设计(BBD)建立了AoR与4个显著性参数间的二次多项式回归模型。依据二次多项式回归模型对目标响应进行预测,得到最优参数组合。以此为基础对壤土AoR进行离散元仿真,AoR数值计算结果(45.4°)与试验结果(44.6°)相对误差为1.79%。最后,选取含水率分别为44.4%、48.7%的壤土进行堆积角仿真模拟,计算结果与堆积试验相对误差分别为2.8%、7.14%。研究表明:回归模型可以根据壤土含水率或AoR预测长江中游地区水田壤土的相关本征参数和接触参数。展开更多
基金Supported by the National Natural Science Foundation of China(11971458,11471310)。
文摘In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.
文摘The concept of TNT(Trinitrotoluene,C_7H_5N_3O_6)equivalence is often invoked to evaluate the performance and predict the explosion parameters of different types of explosives.However,due to its low prediction accuracy and limited application range,the use of TNT equivalence for predicting explosion parameters in a confined space is rare.Compared with explosions in free fields,the process of explosive energy release in a confined space is closely related to various factors such as oxygen balance,combustible components content,and surrounding oxygen content.Studies have shown that in a confined space,negative oxygen balance explosives react with surrounding oxygen during afterburning,resulting in additional energy release and enhanced blast effects.The mechanism of energy release during afterburning is highly complex,making it challenging to determine the TNT equivalence for blast effects in a confined space.Therefore,this remains an active area of research.In this study,internal blast experiments were conducted using TNT and three other explosives under both air and N_2(Nitrogen)conditions to obtain explosion parameters including blast wave overpressure,quasi-static pressure,and temperature.The influences of oxygen balance and external oxygen content on energy release are analyzed.The author proposes principles for determining TNT equivalence for internal explosions while verifying the accuracy of obtained blast parameters through calculations based on TNT equivalence.These findings can serve as references for predicting blast performance.
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
基金partially supported by the Natural Science Foundation of China (Grant Nos.62103052,52272358)partially supported by the Beijing Institute of Technology Research Fund Program for Young Scholars。
文摘This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.
基金supported by the National Natural Science Foundation of China(61701140).
文摘To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on the target detection performance,firstly,a spatial detection model of distributed high-frequency surface wave radar(distributed-HFSWR)is established in this paper.In this model,a method for accurate extraction of direct wave spectrum based on curve fitting is proposed to obtain accurate system internal delay and frequency synchronization error under complex electromagnetic environment background and low signal to noise ratio(SNR),and to compensate for the shift of range and Doppler frequency caused by time-frequency synchronization error.The direct wave component is extracted from the spectrum,the range estimation error and Doppler estimation error are reduced by the method of curve fitting,and the fitting accuracy of the parameters is improved.Then,the influence of frequency synchronization error on target range and radial Doppler velocity is quantitatively analyzed.The relationship between frequency synchronization error and radial Doppler velocity shift and range shift is given.Finally,the system synchronization parameters of the trial distributed-HFSWR are obtained by the proposed spectrum extraction method based on curve fitting,the experimental data is compensated to correct the shift of the target,and finally the correct target parameter information is obtained.Simulations and experimental results demonstrate the superiority and correctness of the proposed method,theoretical derivation and detection model proposed in this paper.
文摘In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LSTM) neural network is nested into the extended Kalman filter(EKF) to modify the Kalman gain such that the filtering performance is improved in the presence of large model uncertainties. To avoid the unstable network output caused by the abrupt changes of system states,an adaptive correction factor is introduced to correct the network output online. In the process of training the network, a multi-gradient descent learning mode is proposed to better fit the internal state of the system, and a rolling training is used to implement an online prediction logic. Based on the Lyapunov second method, we discuss the stability of the system, the result shows that when the training error of neural network is sufficiently small, the system is asymptotically stable. With its application to the estimation of time-varying parameters of a missile dual control system, the LSTM-EKF shows better filtering performance than the EKF and adaptive EKF(AEKF) when there exist large uncertainties in the system model.
文摘为研究农业机械与水田壤土间的相互作用,需获取水田壤土的物理及接触参数。结合物理堆积试验,以休止角作为响应值,采用离散元法(DEM)并选取Hertz-Mindlin with JKR(Johnson-Kendall-Roberts)接触模型对长江中游地区水田壤土展开参数标定研究。首先,通过物理堆积试验获取了壤土休止角(AoR)与含水率间的定量关系,由不同含水率土壤的堆积结果筛分出4种代表性堆积形态,由于水田壤土堆积体轮廓外形比较独特,因此仅对其左右两侧轮廓采用三次多项式进行局部拟合,计算其休止角。以长江中游地区水田壤土成因和预试验为依据来确定其离散元模型中9个参数的高低水平值,通过Plackett-Burman试验设计进行方差分析,发现壤土剪切模量、壤土间动摩擦因数、壤土与不锈钢间静摩擦因数和JKR表面能对AoR影响明显。然后,采用基于响应面法(RSM)原理的Box-Behnken试验设计(BBD)建立了AoR与4个显著性参数间的二次多项式回归模型。依据二次多项式回归模型对目标响应进行预测,得到最优参数组合。以此为基础对壤土AoR进行离散元仿真,AoR数值计算结果(45.4°)与试验结果(44.6°)相对误差为1.79%。最后,选取含水率分别为44.4%、48.7%的壤土进行堆积角仿真模拟,计算结果与堆积试验相对误差分别为2.8%、7.14%。研究表明:回归模型可以根据壤土含水率或AoR预测长江中游地区水田壤土的相关本征参数和接触参数。
