制导参量的估计方法

为了对机动目标实施有效的垂直命中攻击,必须对制导参量进行估计．作者根据实际战斗条件下目标机动特性以及导出参量的噪声性质,对有色噪声进行了白化处理,并给出了机动目标速度、加速度的自适应滤波算法．该方法可有效提高制导参量的估计精度．     

近程空中目标航路研究

本文在等加速俯冲飞行假定下．分析了近程空中目标航路的特点，并据此提出了目标航路模型．经过投影变换，把目标航路模型转化为二次函数．从而使目标航路的滤波及预报问题得到简化．采用进推最小二乘(RLS)原理．给出了目标航路的在线滤波器及预报器．最后．对本文方法进行了仿真．并对仿真结果进行了分析．     

近程空中目标航路研究

本文在等加速俯冲飞行假定下，分析了近程空中目标航路的特点，并据此提出了目标航路模型．经过投影变换，把目标航路模型转化为二次函数，从而使目标航路的滤波及预报问题得到简化．采用递推最小二乘（ＲＬＳ）原理，给出了目标航路的在线滤波器及预报器．最后，对本文方法进行了仿真，并对仿真结果进行了分析．     

基于方向信息测度的图像边缘检测

边缘检测是图像处理中—个重要的研究课题．针对传统图像边缘检测算法对噪声敏感的问题,本文在分析图像像素灰度信息的基础上,建立了—个改进的确定方向信息测度的方法,并利用震动滤波对边缘检测图像进行增强,该方法在滤除噪声的同时,能有效地保留图像的基本目标信息,正确提取图像的边缘．     

一种简化非线性滤波

对非线性系统的状态估计通常采用推广卡尔曼滤波,但由于此方法计算量大、往往在实际工程中不能实时处理,为此,对推广卡尔曼滤波提出了不少简化方法。如解耦滤波及改进α—β—γ滤波等(参见[2])。 本文提出的方法将系统进一步简化为满足稳态滤波条件的定常系统,计算量大大减少;经实际模拟计算,滤波精度可达相当高的水平。 该方法可用于地面电影经纬仪或雷达对飞行目标的自动限综。     

地震动瞬时谱估计的UnscentedKalman滤波方法

用时变ARMA模型描述地震动时程,提出了采用Unscented Kalman滤波技术实现地震动瞬时谱估计的思路．算例分析表明,Unscented Kalman滤波方法较Kalman滤波方法适用范围广,具有较高的时间和频率分辨率,能够更好地跟踪地震动的局部特性,适合处理非线性模型或有突变特性的模型的辨识问题．不同阶数ARMA模型的估计结果还表明,以往被忽略的ARMA模型的理论频率分辨力对地震动瞬时谱估计精度有重要影响,应作为一个参考指标在ARMA模型的判阶中加以考虑．     

近程空中目标航路研究

本文在等加速俯冲飞行假定下,分析了近程空中目标航路的特点,并据此提出了目标航路模型.经过投影变换,把目标航路模型转化为二次函数,从而使目标航路的滤波及预报问题得到简化,采用弟推最小二乘(RLS)原理,给出了目标航路的滤波器及预报器,最后,对本文方法进行了仿真,并对仿真结果进行了分析.     

机动目标的跟踪与反跟踪建模研究

针对机动目标跟踪建模及目标机动规律分析问题,首先建立了基于Kalman滤波的Singer模型和修正的当前模型并利用MATLAB对其进行了求解,然后给出了两种模型下的目标的机动规律.针对飞行目标的航迹关联问题,首先建立了基于直观法的航迹起始模型,然后分别建立基于特征判决的最近邻域航迹关联模型和基于Kalman滤波的航迹关联模型并求解,结果显示,两种航迹关联模型都能较好实现航迹的分离.最后,针对高速机动目标跟踪与航迹预测问题,提出了一种基于初值的Singer模型并分析了高速机动目标的机动规律,然后分别建立了基于空间曲线拟合和基于Kalman滤波的航迹预测模型,并对两种模型进行求解与分析.     

基于方根分解形式的带衰减因子UKF算法应用

UKF作为一种新的非线性滤波方法已在目标跟踪问题中得到应用,在状态的时间更新阶段直接使用非线性模型,不引入线性化误差,而且不必计算Jacobians矩阵.提出了一种基于方根分解形式的带有衰减因子的UKF算法(SRDMA-UKF),算法的方根形式增加了数字稳定性和状态协方差的半正定性.通过衰减因子的引入加强对当前测量数据的利用,减小历史数据对滤波的影响.仿真实验结果表明,该算法与UKF算法相比具有更好的滤波性能.     

由二元生成子群确定的性质

我们记群类x∈TD,若x满足下面性质:“G∈x当且仅当G的每个二元生成子群G_1∈x”文中我们通过对极小反例的分析及扩张方式得到一个较一般的判定TD性质的方法。使一些已知群类的TD性质能非常简单地证明并通过扩张可知大多数常见的子群闭的群类都具有TD性质。     

Sufficiency theorems for target capture

A dynamical system is assumed to be governed by a set of ordinary differential equations subject to control. The set of points in state space from which there exist permissible controls that can transfer these points to a prescribed target set in a finite time interval is called a capture set. The task of determining the capture set is studied in two contexts. first, in the case of the system subject to a single control vector; and second, in the case of the system subject to two control vectors each operated independently. In the latter case, it is assumed that one controller's aim is to cause the system to attain the target, and the other's is to prevent that from occurring.Sufficient conditions are developed that, when satisfied everywhere on the interior of some subset of the state space, ensure that this subset is truly a capture set. A candidate capture set is assumed to have already been predetermined by independent methods. The sufficient conditions developed herein require the use of an auxiliary scalar function of the state, similar to a Lyapunov function.To ensure capture, five conditions must be satisfied. Four of these constrain the auxiliary state function. Basically, these four conditions require that the boundary of the controllable set be an envelope of the auxiliary state function and that that function be positive inside the capture set, approaching zero value as the target set is approached. The final condition tests the inner product of the gradient of the auxiliary state function with the system state velocity vector. If the sign of that inner product can be made negative everywhere within the test subset, then that subset is a capture set.Dedicated to Professor A. BusemannThe authors are indebted to Professors G. Leitmann and J. M. Skowronskii for their useful comments and discussion.     

Target torque estimation for gearshift in dual clutch transmission with uncertain parameters

The target torque of engaging clutches during gearshift is a key factor that affects the dynamic response of powertrains equipped with the dual clutch transmissions (DCT). This paper investigates a method to estimate the target torque of engaging clutches under conditions where engine torque and measurement signals contain white noise and some vehicle parameters (the radius of wheel and rolling friction coefficient) are uncertain. To compute the target torque accurately, the state of system should be estimated when the uncertain parameters exist. The vehicle powertrain is modeled as the 3DOF system when one clutch is closed and the 4DOF system when two clutches are open, while the measured signals include speeds of the engine, transmission, and vehicle (rotational speed of wheels). In addition to traditional extended Kalman filter (EKF), both the joint extended Kalman filter (JEKF) and dual extended Kalman filter (DEKF) are used to estimate the target torque. The simulation results show that DEKF and JEKF provide much higher accuracy in the estimation of target torque than EKF when some parameters of the model are uncertain, so as to produce a better ride performance of the transmission during gearshift, i.e. reduction of power interruption and compressed shifting time. Furthermore, the DEKF provides higher accuracy than the JEKF in estimating uncertain parameters.     

Constrained Markov decision processes with first passage criteria

This paper deals with constrained Markov decision processes (MDPs) with first passage criteria. The objective is to maximize the expected reward obtained during a first passage time to some target set, and a constraint is imposed on the associated expected cost over this first passage time. The state space is denumerable, and the rewards/costs are possibly unbounded. In addition, the discount factor is state-action dependent and is allowed to be equal to one. We develop suitable conditions for the existence of a constrained optimal policy, which are generalizations of those for constrained MDPs with the standard discount criteria. Moreover, it is revealed that the constrained optimal policy randomizes between two stationary policies differing in at most one state. Finally, we use a controlled queueing system to illustrate our results, which exhibits some advantage of our optimality conditions.     

Asymptotical feedback controllability of continuous-time probabilistic logic control networks

In this article, we study the controllability of continuous-time probabilistic logic control networks (CT-PLCNs) under sampled-data feedback controls (SDFCs). First, we demonstrate that the concept of finite-time controllability with probability one for discrete-time probabilistic logic control networks cannot be generalized to CT-PLCNs. Then, we propose the concepts of asymptotical feedback reachability and asymptotical feedback controllability for CT-PLCNs. Based on the invariant subsets, we prove that a target state is asymptotically feedback reachable if and only if the target state is a control equilibrium point and any initial state has an admissible path to the target state. Moreover, we introduce the concept of reachability matrix and propose an easily verifiable criterion for asymptotical feedback reachability expressed in terms of the reachability matrix. Based on these, we prove that a CT-PLCN is asymptotically feedback controllable if and only if every state is a control equilibrium point and there is an admissible path between any pair of initial and target states. The relation between controllability and stabilizability is also discussed. We prove that a CT-PLCN is asymptotically feedback controllable if and only if every state is asymptotically feedback stabilizable. For a controllable CT-PLCN, we propose an algorithm of designing a stabilizing SDFC for any given target state. Additionally, we discuss the asymptotical feedback controllability of CT-PLCNs under time-varying nonuniform SDFCs. Finally, an illustrative example is presented to explain the proposed methods and verify the controllability criteria.     

无消相干子空间中开放量子系统状态调控的收敛性

基于Lyapunov方法提出实现开放量子系统中目标态为无消相干子空间中纯态时收敛的控制策略.在假定被控系统哈密顿量各个本征态的能级差互不相同并且任意能级都是直接耦合的前提下,给出了一个关于观测算符的充分条件使系统最大不变集只包含目标态.选择观测算符平均值为Lyapunov函数,在相互作用绘景下设计控制律,并利用Barbalat引理分析系统的最大不变集.证明了如果满足所提条件,无消相干子空间中系统的任意本征态或叠加态的目标态都是全局渐近稳定的;被控系统能够从任意初始态转移到期望的目标态.同时给出了一种利用Schmidt正交化来构造观测算符的方法,并且在一个三能级系统的仿真实验上验证了所提方法的正确性.     

离散时间马氏决策过程的首达目标准则

本文考虑可数状态离散时间马氏决策过程的首达目标模型的风险概率准则.优化的准则是最小化系统首次到达目标状态集的时间不超过某阈值的风险概率.首先建立最优方程并且证明最优值函数和最优方程的解对应,然后讨论了最优策略的一些性质,并进一步给出了最优平稳策略存在的条件,最后用一个例子说明我们的结果.     

Bilinear minimax control problems for a class of parabolic systems with applications to control of nuclear reactors

This paper considers the bilinear minimax control problem of an important class of parabolic systems with Robin boundary conditions. Such systems are linear on state variables when the control and disturbance are fixed, and linear on the control or disturbance when the state variables are fixed. The objective is to maintain target state variables by taking account the influence of noises in data, while a desired power level and adjustment costs are taken into consideration. Firstly we introduce some classes of bilinear systems and obtain the existence and the uniqueness of the solution, as well as stability under mild assumptions. Afterwards the minimax control problem is formulated. We show the existence of an optimal solution, and we also find necessary optimality conditions. Finally, to illustrate the abstract results, we present two examples of neutron fission systems.     

Performance Analysis for Controlled Semi-Markov Systems with Application to Maintenance

This paper concerns with the performance analysis for controlled semi-Markov systems in Borel state and action spaces. The performability of the system is defined as the probability that the system reaches a prescribed reward level during a first passage time to some target set. Under mild conditions, we develop a value iteration algorithm for computing the optimal value, and establish the existence of optimal policies with the maximal performability. Our main results are applied to a maintenance problem.     

Differential guidance game with incomplete information on the state coordinates and unknown initial state

We study the problem of guaranteed positional guidance of a linear partially observable control system to a convex target set at a given time. The problem is considered in the case of incomplete information. More precisely, it is assumed that the system is subjected to some unknown disturbance; in addition, the initial state is unknown as well. But the sets of admissible disturbances and the set of admissible initial states are known. The latter is assumed to be finite. We construct an algorithm for solving this problem.     

基于矩阵逻辑方程的识别对象状态转化研究

进行错误识别,首先我们需要研究识别的对象.因此,研究首先将错误识别对象分为识别状态、真是状态、应该状态和目标状态等四种状态,并且讨论了几种类型之间的关系.最后运用矩阵逻辑方程求解了识别状态转化为目标状态的转化方式.