Precise asymptotics for the first moment of the error variance estimator in linear models

Let σ² be the unknown error variance of a linear model and let be the estimator of σ² based on the residual sum of squares. In this work, we show the precise asymptotics in the law of the logarithm for the first moment of the error variance estimator.     

Precise asymptotics of error variance estimator in partially linear models

In this paper, we focus our attention on the precise asymptotics of error variance estimator in partially linear regression models, y _i = x _i ^τ β + g(t _i ) + ε _i , 1 ≤ i ≤ n, {ε _i , i = 1, ⋯ n} are i.i.d random errors with mean 0 and positive finite variance σ ². Following the ideas of Allan Gut and Aurel Spătaru^[7,8] and Zhang^[21], on precise asymptotics in the Baum-Katz and Davis laws of large numbers and precise rate in laws of the iterated logarithm, respectively, and subject to some regular conditions, we obtain the corresponding results in partially linear regression models.      

时变参数时滞减振控制研究

时滞动力吸振器对谐波激励有着良好的减振控制效果,但对随机激励的减振控制效果却并不明显,具体表现为时滞动力吸振器对随机激励的减振控制效果与被动吸振器几乎相同。针对上述问题,本文提出了一种新的时变参数时滞减振控制方法。在原有时滞减振控制方法的基础上,首先将时滞增益系数由定值形式变为时间函数形式,然后通过时变优化得到多组时滞控制参数并使其以一定时间周期循环作用于减振控制过程,通过这种方法进一步改善了时滞动力吸振器减振性能。本文最后以二自由度时滞动力吸振器减振模型为例,以主系统的振动响应为仿真对象,运用精细积分法求解了具有时变时滞参数的时滞动力学方程,以此得到了在谐波激励和随机激励作用下主系统振动的时域仿真结果。研究结果表明,在时变参数时滞动力吸振器的控制下,主系统无论是受谐波激励作用还是受随机激励作用,其振动位移、振动速度和振动加速度均比在定值参数时滞动力吸振器控制下时有大幅的减少,时滞动力吸振器的减振性能有了明显的改善。      

带有时滞正则项的图像处理模型近似格式的收敛性

In this paper, the model of image processing with time-delay regularization is considered. A difference scheme is constructed. In the difference scheme,the denominator may be zero in the diffusion, though the term is bounded. Using the related theory of viscosity solution, the convergence is proved.     

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针对链式维护机械臂(EAMA)运行环境的特殊性,对其伺服控制系统进行设计和实现.在控制结构上,系统在基于分布式控制结构的基础上采用了一种新的伺服系统解决方案.在控制策略上选用了高性能PIC单片机进行了硬件电路的设计,并采用了位置、速度双闭环控制算法以实现对机械臂的每个关节的高精度位置伺服控制.通过实验验证了该系统能够满足机械臂的运行要求,且具有良好的动态性能和稳态性能.     

EAST链式维护机械臂伺服控制系统设计

针对链式维护机械臂(EAMA)运行环境的特殊性,对其伺服控制系统进行设计和实现。在控制结构上,系统在基于分布式控制结构的基础上采用了一种新的伺服系统解决方案。在控制策略上选用了高性能PIC单片机进行了硬件电路的设计,并采用了位置、速度双闭环控制算法以实现对机械臂的每个关节的高精度位置伺服控制。通过实验验证了该系统能够满足机械臂的运行要求,且具有良好的动态性能和稳态性能。     

High order symplectic conservative perturbation method for time-varying Hamiltonian system

This paper presents a high order symplectic conservative perturbation method for linear time-varying Hamiltonian system.Firstly,the dynamic equation of Hamiltonian system is gradually changed into a high order perturbation equation,which is solved approximately by resolving the Hamiltonian coefficient matrix into a "major component" and a "high order small quantity" and using perturbation transformation technique,then the solution to the original equation of Hamiltonian system is determined through a series of inverse transform.Because the transfer matrix determined by the method in this paper is the product of a series of exponential matrixes,the transfer matrix is a symplectic matrix;furthermore,the exponential matrices can be calculated accurately by the precise time integration method,so the method presented in this paper has fine accuracy,efficiency and stability.The examples show that the proposed method can also give good results even though a large time step is selected,and with the increase of the perturbation order,the perturbation solutions tend to exact solutions rapidly.     

Precise large deviations for widely orthant dependent random variables with dominatedly varying tails

For the widely orthant dependent (WOD) structure, this paper mainly investigates the precise large deviations for the partial sums ofWOD and non-identically distributed random variables with dominatedly varying tails. The obtained results extend some corresponding results.     

不确定时滞混沌系统的自适应动态神经网络控制

研究了一类具有不确定时滞的非自治混沌系统的控制问题. 通过结合Lyapunov-Krasovskii函数和Lyapunov函数设计参数可调的不确定时滞补偿器,使得反馈控制输入信号不受时延的影响;同时引入动态结构自适应神经网络,以消除系统的不确定性,其隐层神经元的个数可以随着逼近误差的增大而自适应增加,改善了逼近速度与网络复杂度的关系;最后,用Duffing混沌系统的控制仿真示例表明该方法的有效性. 关键词： 混沌系统 自适应控制 不确定时滞 动态结构神经网络     

Global exponential synchronization between Lü system and Chen system with unknown parameters and channel time-delay

This paper proposes a nonlinear feedback control method to realize global exponential synchronization with channel time-delay between the Lü system and Chen system,which are regarded as the drive system and the response system respectively.Some effective observers are produced to identify the unknown parameters of the Lü system.Based on the Lyapunov stability theory and linear matrix inequality technique,some sufficient conditions of global exponential synchronization of the two chaotic systems are derived.Simulation results show the effectiveness and feasibility of the proposed controller.