时间依赖的网络中最小时间路径算法

时间依赖的网络与传统网络模型相比更具有现实意义，具有广泛的应用领域，交通网络和通信网络可以抽象为时间依赖的网络模型，当模型中弧的工度是时间依赖的变量，最短路径问题的求解变得非常困难，早期的研究者通过具体的网络实例认识到传统最短路径算法在这种情况下是不正确的，因此给出限制性条件使得传统最短路径算法是有效的。该文从最短路径算法的理论基础入手，从理论上证明了传统最短路径算法，如Dijkstra算法和标号设置算法，在时间依赖的网络上不能有效地求解最短路径问题，并且，在没有任何限制性条件下，给出了时间依赖的网络模型，理论基础，求解最小时间路径的优化条件和SPTDN算法，从理论上证明了SPTDN算法的正确性，算法的实验结果是正确的，最后给出了时间依赖的网络应用实例。     

基于连续体模型的电力系统频率动态研究

针对电力系统连续体建模过程中发电机参数分配存在的复杂性较大的问题,提出了一种基于最短路径的连续体模型参数分配方法。该方法首先通过摇摆方程将传统离散系统连续化,并根据本文设计的算法计算得到存在扰动的发电机到剩余发电机的所有路径,选取扰动传播的最短路径,并将发电机惯性常数平均分配到各最短路径。每条最短路径上再采用高斯分配法将分配得到的参数进行再次分配,给出了参数分配过程中的准确表达式。通过对New England 10机39节点标准数据集进行算例仿真可知,从扰动源出发到各发电机的传播路径数量庞大,参数分配复杂度很大。通过选取各对应的9条最短路径进行参数分配,大大降低了参数分配的计算复杂度,同时使得对整个系统的分析和描述更加准确。     

最短路径重构算法

研究了在Ｎ个顶点的图中，仅给出了所有顶点对之间最短路径距离矩阵，而计算任两顶点间最短路径问题。这种算法因没有利用原始图中有关边的信息，被称为重构算法。本研究取得了如下成果：①在单一的顶点对之间最短路径重构的时间复杂度为Ｏ（ｎｌｏｇｎ）；②在所有顶点对之间的最短路径重构的时间复杂度为Ｏ（ｎ＾３）；③在带有ｎ／ｌｏｇｎ个处理器的独占读写并行随机访问器上，单一顶点对之间的最短路径重构时间复杂度为Ｏ（（ｌ     

非线性离散系统的反馈线性化

本文研究一类多输入非线性离散系统的线性化问题，给出了非线性离散系统状态反馈线性化的充要条件。     

三阶时变离散系统的一致渐近稳定性

首先分析了研究三阶时变离散系统稳定性的必要性，然后定量地给出了三阶线性时变离散系统和一类非线性三阶时变离散系统一致渐近稳定的判据，从而为基于特征建模设计适当的控制律以满足稳定性的要求提供了理论依据。     

信息化助力服务取胜——解析上海市徐汇区中心医院PACS系统建设

挂号时间长、候诊时间长、取药时间长，就诊时间短，这个称为“三长一短”的现象一直是人们上医院看病时最头疼也最无奈的问题。很多时候，我们花半天时间去看病，也许真正医生诊断的时间只有十分钟，大部分时间都是花在排队等候上。位于上海市中心繁华地段——淮海路上的徐汇区中心医院在业内首创的“一门式服务”为打破这一“痼疾”做出了有益的尝试，     

四阶时变离散系统的一致渐近稳定性

特征建模的方法为智能控制器设计和利用低阶控制器控制一些高阶对象提供了理论依据。基于特征模型设计的自适应控制方案，其稳定性分析实际上归结为时变离散系统的稳定性问题，目前尚无实用性判据。对于速度跟踪和加速度控制，基于特征模型设计的自适应控制方案其稳定性问题即为四阶时变离散系统的稳定性问题，文中利用Lyapunov直接方法定量给出了四阶线性时变离散系统和一类非线性四阶时变离散系统一致渐近稳定的判据，所给判据仅依赖于系数的变化范围和系数本身改变量的范围。     

状态空间模式采样控制系统的鲁棒稳定性

本文基于状态空间模式的采样控制系统，给出连续控制对象产生和不确定性时，闭环离散系统鲁棒稳定的一个充分条件，对于采样系统中非线性不确定性结构。是采用谱范数估计等效离散系统扰动来处理的。     

离散系统仿真技术研究

针对离散系统仿真基本技术特点，文章重点对系统仿真程序结构，软件模块组织，以及ＧＰＳＳ－Ｆ仿真语言使用特点和存在问题进行了研究。文章可对离散系统仿真设计提供参考。     

双线性离散系统的离散Walsh级数分析法

本文采用了离散Walsh级数分析了双线性离散系统，并给出了相应的算法，由于离散Walsh级数分析可直接借助于计算机来分析，所以可节省时间，并有为双线性离散系统的分析提供了新手段。     

基于独立成分分析的状态监控方法

针对目前部分的工业系统存在系统模型或系统独立变量不确定的情况,提出了一种基于独立成分分析(Independent Component Analysis,ICA)的状态监控方法。该方法不需要有关系统模型和系统变量的先验知识,解决了系统模型或系统变量不确定的问题。运用独立成分分析法对系统的观测信号进行特征提取,通过监控分离得到的特征信号来实现对整个系统的状态进行监控。分别对一个离散系统和一个双容水箱液位系统进行仿真验证,仿真结果表明该方法能够有效地实现系统监控。     

State transfer based on decoherence-free target state by Lyapunov-based control

We propose a Lyapunov-based control approach for state transfer based on the decoherence-free target state.The expected target state is constructed to be a decoherence-free state in a decoherence-free subspace(DFS) by an external laser fieldⅠ,so that the system state can be decoupled from the environment,and no more decoherence process will occur.With the decoherence-free target state,we design a Lyapunov-based control fieldⅡto steer the given initial state to the decoherence-free state of open quantum systems as completely as possible,and decouple the system state from the environment at the same time.In the end,it is verified that the state transfer control designed comes true on a∧-type four-level atomic system,and the system can stay on the decoherence-free target state without coupling to environment.     

Set-Theoretic Estimation of Hybrid System Configurations

Hybrid systems serve as a powerful modeling paradigm for representing complex continuous controlled systems that exhibit discrete switches in their dynamics. The system and the models of the system are nondeterministic due to operation in uncertain environment. Bayesian belief update approaches to stochastic hybrid system state estimation face a blow up in the number of state estimates. Therefore, most popular techniques try to maintain an approximation of the true belief state by either sampling or maintaining a limited number of trajectories. These limitations can be avoided by using bounded intervals to represent the state uncertainty. This alternative leads to splitting the continuous state space into a finite set of possibly overlapping geometrical regions that together with the system modes form configurations of the hybrid system. As a consequence, the true system state can be captured by a finite number of hybrid configurations. A set of dedicated algorithms that can efficiently compute these configurations is detailed. Results are presented on two systems of the hybrid system literature.      

基于状态距离的量子控制策略

基于Bures距离,选择一个表征量子系统期望态和实际态间距离的Lyapunov函数.考虑到初始态与期望态分别正交和不正交的情况,提出一类带有状态反馈的控制策略,它可以保证闭环控制系统的稳定性.特别详细地分析、推导和证明了系统的渐进稳定性.最后,在一个自旋1/2粒子系统上进行了仿真实验,分析了不同参数情况下系统的状态演化时间和控制值间的关系.研究结果对于量子系统的控制具有一般理论意义.     

A theory of state covariance assignment for discrete systems

In many regulation control problems it is desired to design the controller so that various system states have acceptable root mean squared values. This is a multiple objective problem. One way to satisfy these objectives is to assign a specified state covariance to the system. This paper introduces and solves the following problem: 1) characterize the entire set of state covariances which may be assigned to a linear discrete-time system by state feedback; and 2) find the set of all state feedback gains which will assign an admissible state covariance to the system. Extensions are also presented for state estimate feedback.     

Entanglement revival can occur only when the system–environment state is not a Markov state

Markov states have been defined for tripartite quantum systems. In this paper, we generalize the definition of the Markov states to arbitrary multipartite case and find the general structure of an important subset of them, which we will call strong Markov states. In addition, we focus on an important property of the Markov states: If the initial state of the whole system–environment is a Markov state, then each localized dynamics of the whole system–environment reduces to a localized subdynamics of the system. This provides us a necessary condition for entanglement revival in an open quantum system: Entanglement revival can occur only when the system–environment state is not a Markov state. To illustrate (a part of) our results, we consider the case that the environment is modeled as classical. In this case, though the correlation between the system and the environment remains classical during the evolution, the change of the state of the system–environment, from its initial Markov state to a state which is not a Markov one, leads to the entanglement revival in the system. This shows that the non-Markovianity of a state is not equivalent to the existence of non-classical correlation in it, in general.     

Subspace-based identification of discrete time-delay system

We investigate the identification problems of a class of linear stochastic time-delay systems with unknown delayed states in this study. A time-delay system is expressed as a delay differential equation with a single delay in the state vector. We first derive an equivalent linear time-invariant (LTI) system for the time-delay system using a state augmentation technique. Then a conventional subspace identification method is used to estimate augmented system matrices and Kalman state sequences up to a similarity transformation. To obtain a state-space model for the time-delay system, an alternate convex search (ACS) algorithm is presented to find a similarity transformation that takes the identified augmented system back to a form so that the time-delay system can be recovered. Finally, we reconstruct the Kalman state sequences based on the similarity transformation. The time-delay system matrices under the same state-space basis can be recovered from the Kalman state sequences and input-output data by solving two least squares problems. Numerical examples are to show the effectiveness of the proposed method.     

Receding-horizon estimation for switching discrete-time linear systems

Receding-horizon state estimation is addressed for a class of discrete-time systems that may switch among different modes taken from a finite set. The system and measurement equations for each mode are assumed to be linear and perfectly known, but the current mode of the system is unknown, the state variables are not perfectly measurable and are affected by disturbances. The system mode is regarded as an unknown discrete state to be estimated together with the continuous state vector. Observability conditions are found to distinguish the system mode in the presence of bounded system and measurement noises. These results allow one to construct an estimator that relies on the combination of the identification of the discrete state with the estimation of the state variables by minimizing a receding-horizon quadratic cost function. The convergence properties of such an estimator are studied, and simulation results are reported to show the effectiveness of the proposed approach.     

随机开放量子系统的纯态开关反馈控制EI北大核心CSCD

针对目标态为纯态的情况,本文对有限维随机开放量子系统,提出一种同时适用于本征态和叠加态的开关控制,它是由常量控制和基于李雅普诺夫方法设计的控制律组成,实现随机开放量子系统的状态转移和收敛控制,其中,李雅普诺夫函数为系统的状态距离,常量控制用来驱动系统状态从初始状态进入含有目标态的收敛域中,李雅普诺夫控制用来使进入收敛域中的状态继续收敛到期望的目标态.将所提出的控制方法,应用于2比特随机开放量子系统进行了数值仿真实验,并与本征态开关控制律方法进行了性能对比,实验结果表明了所提出的控制律的优越性.