Approximate Controllability of Second-Order Neutral Stochastic Differential Equations with Infinite Delay and Poisson Jumps

The modelling of risky asset by stochastic processes with continuous paths, based on Brownian motions, suffers from several defects. First, the path continuity assumption does not seem reasonable in view of the possibility of sudden price variations(jumps) resulting of market crashes. A solution is to use stochastic processes with jumps, that will account for sudden variations of the asset prices. On the other hand, such jump models are generally based on the Poisson random measure. Many popular economic and financial models described by stochastic differential equations with Poisson jumps. This paper deals with the approximate controllability of a class of second-order neutral stochastic differential equations with infinite delay and Poisson jumps. By using the cosine family of operators, stochastic analysis techniques, a new set of sufficient conditions are derived for the approximate controllability of the above control system. An example is provided to illustrate the obtained theory.     

标准型双线性比例——微分变结构系统的循环进位控制

在标准型双线性比例变结构系统循环进位控制的基础上，研究这种系统的比例—微分变结构控制。采用时间采样循环和状态变量循环的双进位控制算法，使系统的微分方程成为能分离变量和递推求解的一阶微分方程组。从减小系统失调误差的最终控制目的出发，提出了状态变量分量的步进置换概念。使用旋转算子表达比例—微分变结构的切换。用统一的时钟信号实现控制策略中的三种变换。给出了控制策略的结构图。     

Exact Controllability of Wave Equations with Interior Degeneracy and One-Sided Boundary Control

In this paper, the authors mainly consider the exact controllability for degenerate wave equation, which degenerates at the interior point, and boundary controls acting at only one of the boundary points. The main results are that, it is possible to control both the position and the velocity at every point of the body and at a certain time T for the wave equation with interior weakly degeneracy.Moreover, it is shown that the exact controllability fails for the wave equation with interior strongl...     

基于Hill方程近地卫星模型预测轨道保持方法

近地卫星偏离标称轨道的过程可以表示为该卫星和一个在标称轨迹上运行的"虚"卫星的相对运动,服从Hill方程。在此基础上建立一种在线控制方法,利用模型预测控制(MPC)进行轨道优化和偏差消除,使用多变量优化的控制算法,将控制量的大小与轨道器的轨道偏差联系起来,形成反馈系统,通过给出开环和前馈-反馈闭环两种形式的控制方程,建立基于甚小推力发动机多次点火的轨道控制方法,从而确定控制量将卫星轨道实时保持在偏差管道内。     

Output Tracking for One-Dimensional Wave Equation with Non-Collocated Control and Output Configuration

This paper considers output tracking for a one-dimensional wave equation with general disturbance which includes both internal nonlinear uncertainty and external disturbance. The performance output is non-collocated to the control. The disturbance is estimated by an essentially extended state observer from active disturbance rejection control and the difficulty caused by the non-collocated configuration of control and output is overcome by a proper trajectory planning. An output feedback law is proposed to make the tracking error be convergent to zero exponentially as time goes to infinity.At the same time, all states of the closed-loop system are shown to be uniformly bounded. Numerical simulation is also presented to validate the theoretical results.     

广义双线性系统的参考模型终端滑模控制

利用李雅普诺夫方法研究了广义双线性系统的参考模型终端滑模控制.首先通过选取适当的非线性切换流形,与相应的终端滑模控制律来设计了广义双线性系统的终端滑模控制方法,保证了其闭环系统的渐近稳定,并使闭环系统模态能够在有限时间内达到平衡点,实现终端滑动模运动.最后,通过了一个数值算例说明了该方法的有效性.     

发汗控制方程差分方法的误差增长分析

本文讨论发汗控制方程差分方法的误差增长，提出了使方法数值稳定的步长控制准则。     

Control for a Class of Stochastic Mechanical Systems Based on the Discrete-Time Approximate Observer

This paper investigates the observer-based control problem of a class of stochastic mechanical systems. The system is modelled as a continuous-time It o stochastic differential equation with a discrete-time output. Euler-Maruyama approximation is used to design the discrete-time approximate observer, and an observer-based feedback controller is derived such that the closed-loop nonlinear system is exponentially stable in the mean-square sense. Also, the authors analyze the convergence of observer error when the discrete-time approximate observer servers as a state observer for the exact system. Finally, a simulation example is used to demonstrate the effectiveness of the proposed method.     

多维发汗控制方程的数学求解

本文给出了多维发汗控制方程的解析解。     

基于导热微分方程新解法的人体温度仿真

传统直角坐标系下的导热微分方程与人体几何特性匹配较差,造成方程求解精确度低,从而引起人体温度仿真值与真实值偏差较大。针对这一问题,文章基于人体椭圆柱体的几何特性,将导热微分方程从直角坐标系转化为椭圆柱坐标系,采用交替方向全隐格式的有限体积法对方程进行离散、求解;同时给定初始温度以及边界条件,对人体温度进行仿真。将本文仿真结果与传统导热微分方程的计算值以及实验值进行对比,得出本文的计算方法正确且计算精度较高。     

奇异系统的取消输出不变子空间和取消输出能控子空间

本文针对具有直接控制馈入的奇异系统, 研究了与之输出零化有关的不变子空间及能子空间, 引入了奇异系统的取消输出不变子空间及取消输出能控子空间的概念, 并且讨论了这两种子空间的性质及其相互关系, 得到了Wonham有关正常系统的(A, B)不变子空间和(A, B)能控子空间的平行结果。本文的结果为解决带有直接控制馈入的奇异系统的反馈综合问题提供了理论基础。     

Fractal Solitons,Arbitrary Function Solutions,Exact Periodic Wave and Breathers for a Nonlinear Partial Differential Equation by Using Bilinear Neural Network Method

This paper extends a method, called bilinear neural network method(BNNM), to solve exact solutions to nonlinear partial differential equation. New, test functions are constructed by using this method. These test functions are composed of specific activation functions of single-layer model,specific activation functions of "2-2" model and arbitrary functions of "2-2-3" model. By means of the BNNM, nineteen sets of exact analytical solutions and twenty-four arbitrary function solutions of the dimensionally reduced p-gB KP equation are obtained via symbolic computation with the help of Maple. The fractal solitons waves are obtained by choosing appropriate values and the self-similar characteristics of these waves are observed by reducing the observation range and amplifying the partial picture. By giving a specific activation function in the single layer neural network model, exact periodic waves and breathers are obtained. Via various three-dimensional plots, contour plots and density plots,the evolution characteristic of these waves are exhibited.     

An Inverse Problem of an Unknown Source in a Heat Equation

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Variable Selection for Structural Equation with Endogeneity

This paper studies variable selection problem in structural equation of a two-stage least squares (2SLS) model in presence of endogeneity which is commonly encountered in empirical economic studies. Model uncertainty and variable selection in the structural equation is an important issue as described in Andrews and Lu (2001) and Caner (2009). The authors propose an adaptive Lasso 2SLS estimator for linear structural equation with endogeneity and show that it enjoys the oracle properties, i.e., the consistency in both estimation and model selection. In Monte Carlo simulations, the authors demonstrate that the proposed estimator has smaller bias and MSE compared with the bridge-type GMM estimator (Caner, 2009). In a case study, the authors revisit the classic returns to education problem (Angrist and Krueger, 1991) using the China Population census data. The authors find that the education level not only has strong effects on income but also shows heterogeneity in different age cohorts.     

On Almost Controllability of Dynamical Complex Networks with Noises

This paper discusses the controllability problem of complex networks. It is shown that almost any weighted complex network with noise on the strength of communication links is controllable in the sense of Kalman controllability. The concept of almost controllability is elaborated by both theoretical discussions and experimental verifications.     

An Efficient Constrained Model Predictive Control Algorithm Based on Approximate Computation

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GPC隐式算法及其在供热控制中的仿真研究

基于理论研究和工程应用的需要，提出了广义预测隐式算法。首先介绍了具有滤波器的模型已知的基本广义预测控制（GPC）算法，然后给出了两种隐式自适应算法，一种是已知对象阶跃响应前P个参数的算法，这种算法既不需要在线递推求解Diophantine方程，也不需在线求逆；另一种是一次辨识控制器参数的算法。最后以集中供热热力站热交换过程为应用背景，对基本算法和两种隐式算法进行仿真研究，其结果证明了算法的有效性。     

Controllability and observability of networked control systems with time-varying delays

The controllability and observability of networked control systems are studied. Aiming at the networked control system with time-varying delay, the sufficient and necessary conditions for complete controllability and complete observability of the system are presented, respectively. Because of Markov characteristic of the network-induced delay, in terms of stochastic theory, a sufficient and necessary condition for completely mean value controllability of networked control systems is obtained. Further, the conditions that the controllability and observability of networked control systems are equivalent to the initial time-invariant system are given. Controllability and observability realization indexes are also discussed, respectively. The numerical example demonstrates the effectiveness of the proposed theory.     

Lindblad型开放量子系统最优控制

对于伴随着松弛和耗散的Lindblad型开放量子系统,采用基于Liouville超算符变换的方法,将开放量子系统的动力学微分方程的矩阵表达形式转化成向量表达以简化微分方程的求解。以系统被控状态到达目标状态的期望值为性能指标,对变换后的开放量子系统进行最优控制律的设计,以达到状态转移的目的。在MATLAB环境下以2能级开放量子系统为例进行了系统仿真实验。对控制参数的变化对系统的布居数转移概率及其控制时间的影响进行了对比实验,并对实验结果进行了对比分析。

Abstract：

In order to solve the state of an open quantum system with relaxation and dissipation,the dynamical equation of the system in matrix was transformed into vector form in Liouville space. Taking the expectation value for the state under control reaching the target state as performance indicators,an optimal control function was derived for the system transformed. The control a 2-level open quantum system was simulated on in MATLAB. The influence to population transfer probability and control time caused by changing of parameters were analysed contrastively.     

Approximate conditional likelihood for generalized linear models with general missing data mechanism

The generalized linear model is an indispensable tool for analyzing non-Gaussian response data, with both canonical and non-canonical link functions comprehensively used. When missing values are present, many existing methods in the literature heavily depend on an unverifiable assumption of the missing data mechanism, and they fail when the assumption is violated. This paper proposes a missing data mechanism that is as generally applicable as possible, which includes both ignorable and nonignorable missing data cases, as well as both scenarios of missing values in response and covariate. Under this general missing data mechanism, the authors adopt an approximate conditional likelihood method to estimate unknown parameters. The authors rigorously establish the regularity conditions under which the unknown parameters are identifiable under the approximate conditional likelihood approach. For parameters that are identifiable, the authors prove the asymptotic normality of the estimators obtained by maximizing the approximate conditional likelihood. Some simulation studies are conducted to evaluate finite sample performance of the proposed estimators as well as estimators from some existing methods. Finally, the authors present a biomarker analysis in prostate cancer study to illustrate the proposed method.