FORWARD-BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS, LINEAR QUADRATIC STOCHASTIC OPTIMAL CONTROL AND NONZERO SUM DIFFERENTIAL GAMES

In this paper, we use the solutions of forward-backward stochastic differential equations to get the explicit form of the optimal control for linear quadratic stochastic optimal control problem and the open-loop Nash equilibrium point for nonzero sum differential games problem. We also discuss the solvability of the generalized Riccati equation system and give the linear feedback regulator for the optimal control problem using the solution of this kind of Riccati equation system.     

Backward linear-quadratic stochastic optimal control and nonzero-sum differential game problem with random jumps

This paper studies the existence and uniqueness of solutions of fully coupled forward-backward stochastic differential equations with Brownian motion and random jumps. The result is applied to solve a linear-quadratic optimal control and a nonzero-sum differential game of backward stochastic differential equations. The optimal control and Nash equilibrium point are explicitly derived. Also the solvability of a kind Riccati equations is discussed. All these results develop those of Lim, Zhou (2001) and Yu, Ji (2008).     

STOCHASTIC SYSTEM IDENTIFICATION VIA ADAPTIVE SPECTRAL FACTORIZATION

We consider in this paper the problem of recursive identification for stochastic systemswhen the noise model does not satisfy the positive real condition associated with convergence ofstandard algorithms.To avoid the positive real condition,adaptive spectral factorization techniquesare exploited on the basis of a class of non-standard time-varying recursive Riccati equations.Theasymptotic properties of the Riccati equations are studied as a crucial step to the convergence resultsof the paper.     

Stochastic differential equations and stochastic linear quadratic optimal control problem with Lévy processes

In this paper, the authors first study two kinds of stochastic differential equations (SDEs) with Lévy processes as noise source. Based on the existence and uniqueness of the solutions of these SDEs and multi-dimensional backward stochastic differential equations (BSDEs) driven by Lévy processes, the authors proceed to study a stochastic linear quadratic (LQ) optimal control problem with a Lévy process, where the cost weighting matrices of the state and control are allowed to be indefinite. One kind of new stochastic Riccati equation that involves equality and inequality constraints is derived from the idea of square completion and its solvability is proved to be sufficient for the well-posedness and the existence of optimal control which can be of either state feedback or open-loop form of the LQ problems. Moreover, the authors obtain the existence and uniqueness of the solution to the Riccati equation for some special cases. Finally, two examples are presented to illustrate these theoretical results. This work was supported by the National Basic Research Program of China (973 Program) under Grant No. 2007CB814904, the Natural Science Foundation of China under Grant No. 10671112 and Shandong Province under Grant No. Z2006A01, and Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20060422018.     

基于改进差分进化算法的水文模型参数多目标优选研究

在差分进化算法的基础上, 受马尔可夫链蒙特卡罗方法的启发, 建立了differential evolution adaptive metropolis (DREAM)算法. DREAM 算法融合了马尔可夫链蒙特卡罗方法和差分进化算法的优势, 较好地解决了马尔可夫链蒙特卡罗方法中搜索步长的恰当取值以及搜索方向的准确定位问题, 并能有效解决差分进化算法的群体多样性和收敛速度问题. 在 DREAM 算法基础上, 引入多目标优化思想, 提出了一种基于改进适应度分配策略和外部存档方案的多目标 DREAM 算法, 并应用于岷江流域 CMD-3PAR 降雨-径流模型参数优选研究. 结果表明: 多目标DREAM算法能够找到一组范围宽广、分布均匀且数量充足的 Pareto 最优解供决策者评价优选.     

Maximum principle for partially-observed optimal control problems of stochastic delay systems

This paper is concerned with partially-observed optimal control problems for stochastic delay systems. Combining Girsanov’s theorem with a standard variational technique, the authors obtain a maximum principle on the assumption that the system equation contains time delay and the control domain is convex. The related adjoint processes are characterized as solutions to anticipated backward stochastic differential equations in finite-dimensional spaces. Then, the proposed theoretical result is applied to study partially-observed linear-quadratic optimal control problem for stochastic delay system and an explicit observable control variable is given.     

A Class of Parallel Implicit Runge-Kutta Formulas

A class of parallel implicit Runge-Kutta formulas is constructed for multiprocessor system. A family of parallel implicit two-stage fourth order Runge-Kutta formulas is given. For these formulas, the convergence is proved and the stability analysis is given. The numerical examples demonstrate that these formulas can solve an extensive class of initial value problems for the ordinary differential equations.     

一类并行隐式Runge-Kutta公式

本文针对多处理机系统构造了一类并行隐式Runge-Kutta公式,对2级Runge-Kutta公式给出具有4阶精度的公式族,并证明了它们的收敛性,进行稳定性分析。数值例子表明,该公式可以有效地数值求解较广泛类型的常微分方程初值问题。     

ANTI-PERIODIC SOLUTIONS FOR FIRST AND SECOND ORDER NONLINEAR EVOLUTION EQUATIONS IN BANACH SPACES

In this paper, a new existence theorem of anti-periodic solutions for a class ofstrongly nonlinear evolution equations in Banach spaces is presented. The equations con-tain nonlinear monotone operators and a nonmonotone perturbation. Moreover, throughan appropriate transformation, the existence of anti-periodic solutions for a class of second-order nonlinear evolution equations is verified. Our abstract results are illustrated by anexample from quasi-linear partial differential equations with time anti-periodic conditionsand an example from quasi-linear anti-periodic hyperbolic differential equations.     

An augmented BV setting for feedback switching control

<正> This paper considers dynamical systems under feedback with control actions limited toswitching.The authors wish to understand the closed-loop systems as approximating multi-scale problemsin which the implementation of switching merely acts on a fast scale.Such hybrid dynamicalsystems are extensively studied in the literature,but not much so far for feedback with partial stateobservation.This becomes in particular relevant when the dynamical systems are governed by partialdifferential equations.The authors introduce an augmented BV setting which permits recognition ofcertain fast scale effects and give a corresponding well-posedness result for observations with such minimalregularity.As an application for this setting,the authors show existence of solutions for systemsof semilinear hyperbolic equations under such feedback with pointwise observations.     

Linear Quadratic Regulation for Discrete-Time Systems with Input Delay: Spectral Factorization Approach

The infinite-horizon linear quadratic regulation （LQR） problem is settled for discretetime systems with input delay. With the help of an autoregressive moving average （ARMA） innovation model, solutions to the underlying problem are obtained. The design of the optimal control law involves in resolving one polynomial equation and one spectral factorization. The latter is the major obstacle of the present problem, and the reorganized innovation approach is used to clear it up. The calculation of spectral factorization finally comes down to solving two Riccati equations with the same dimension as the original systems.     

H ∞ filtering for continuous-time systems with pointwise time-varying delay

The problem of H_∞filtering for continuous-time systems with pointwise time-varying delay is investigated in this paper.By applying an innovation analysis in Krein space,a necessary and sufficient condition for the existence of an H_∞filter is derived in two methods:One is the partial differential equation approach,the other is the reorganized innovation analysis approach.The former gives a solution to the proposed H_∞filtering problem in terms of the solution of a partial differential equation with boundary conditions.The later gives an analytical solution to the proposed H_∞filtering problem in terms of the solutions of Riccati and matrix differential equations.     

A Mean-Field Linear-Quadratic Stochastic Stackelberg Differential Game with one Leader and Two Followers

This paper is concerned with a linear-quadratic(LQ) stochastic Stackelberg differential game with one leader and two followers, where the game system is governed by a mean-field stochastic differential equation(MF-SDE). By maximum principle and verification theorem, the open-loop Stackelberg solution is expressed as a feedback form of the state and its mean with the help of three systems of Riccati equations.     

ROBUST KALMAN FILTERING FOR SYSTEMS UNDER NORM BOUNDED UNCERTAINTIES IN ALL SYSTEM MATRICES AND ERROR COVARIANCE CONSTRAINTS

This paper concerns robust Kalman filtering for systems under norm bounded uncertainties in all the system matrices and error covariance constraints. Sufficient conditions are given for the existence of such filters in terms of Riccati equations. The solutions to the conditions can be used to design the filters. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed design procedure.     

Optimal Output Tracking Control and Stabilization of Networked Control Systems with Packet Losses

This paper studies the optimal output tracking control and stabilization for networked control systems with packet losses via output feedback control. Both finite-horizon and infinite-horizon cases are considered. For the finite-horizon case, the authors introduce an augmented system according to the state variable and the reference trajectory for the first time. Based on a set of difference Riccati equations, an optimal output feedback tracking controller is proposed by applying the stochastic maximum principle. And an optimal estimator is presented. For the infinite-horizon case, a necessary and sufficient condition for the stabilization of the system is provided. And an optimal output feedback stabilizing tracking controller is obtained by establishing a set of algebraic Riccati equations. Finally,numerical examples are given to verify the proposed results.     

奇异线性二次型微分鞍点对策的小波逼近解法

研究广义状态系统中线性二次型微分对策鞍点策略的数值求解问题。基于小波多尺度多分辨逼近特性 ,提出了一种数值求解新方法。该法基于Daubechies小波的优良性质 ,特别是将Daubechies小波基的积分运算矩阵、乘积矩阵和快速离散小波变换系数矩阵应用于原问题的主要方程 ,将原问题转化为矩阵代数优化问题 ,避免直接计算耦合Riccati微分方程。算法简洁明了 ,适合于计算机求解。实例计算结果显示 ,该算法是可行的     

基于李普希茨常数估计的混沌鲁里叶系统同步

针对混沌鲁里叶系统同步控制设计中,估计系统不变集和非线性环节李普希茨常数存在的困难,提出在李普希茨常数未知时对其进行自适应估计的思路。在此基础上结合求解一个相应的连续代数里卡提方程,通过李亚普诺夫函数分析方法得到两个混沌鲁里叶系统同步的自适应控制器。仿真实例表明设计的自适应控制器简洁、快速且无超调,具有良好的控制效果。     

多目标决策的逼近方法（Ⅰ）：理论分析

本文将函数序列的ｖ－收敛性（ｖａｒｉａｔｉｏｎａｌｃｏｎｖｅｒｇｅｎｃｅ）推广到向量值函数，在ｖ－收敛性的条件下得到了给定的多目标决策问题的近似弱有效解集的下半连续性并给出了若干容易验证的充分条件．在一致收敛性和不变凸性（ｉｎｖｅｘｉｔｙ）的条件下得到了近似有效解集的连续性．作为本文一般性结果的应用，得到了求解多目标ｍｉｎｉｍａｘ（最小最大）问题的一种有效的逼近方法：极大熵方法的收敛性质．     

Solution to stochastic LQR problem with multiple inputs

This paper considers the stochastic linear quadratic regulation(LQR) problem for It stochastic systems with multiple input controllers. The explicit controllers are given in terms of two Riccati equations by introducing one new costate and establishing the homogeneous relationship between the state and the new costate. More importantly, it is more computation saving for the derived Riccati equations than the one derived by augmentation technique.     

Monotone Iterative Technique for Boundary Value Problem of Second Order Singular Differential System

ＭｏｎｏｔｏｎｅＩｔｅｒａｔｉｖｅＴｅｃｈｎｉｑｕｅｆｏｒＢｏｕｎｄａｒｙＶａｌｕｅＰｒｏｂｌｅｍｏｆＳｅｃｏｎｄＯｒｄｅｒＳｉｎｇｕｌａｒＤｉｆｆｅｒｅｎｔｉａｌＳｙｓｔｅｍＷＡＮＧＷｅｉ；ＬＩＵＹｏｎｇｑｉｎｇ（Ｄｅｐｔ．ｏｆＡｕｔｏｍａｔｉｏｎ...