Finite-Time Stochastic Stability of Random Impulsive Positive System

The paper focuses on the finite-time stochastic stability(FTSS) problems for positive system with random impulses. Combining Lyapunov functions with the probability property of the impulsive interval, first, the sufficient conditions of FTSS for the positive systems affected by one type of random impulses are given; second, the criteria of FTSS for positive systems suffered from multiple types of random impulses are established. Finally, two examples are presented to show the validity of results.     

Stabilization of Continuous-Time Systems Against Stochastic Network Uncertainties: Fundamental Variance Bounds

This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative uncertainties. The authors consider multi-input, multi-output(MIMO) linear time-invariant systems subject to multiple static, structured stochastic uncertainties,and seek to derive fundamental conditions to ensure that a system can be stabilized under a mean-square criterion. In the stochastic control framework, this problem can be considered as one of optimal control under state-or input-dependent random noises, while in the networked control setting, a problem of networked feedback stabilization over lossy communication channels. The authors adopt a mean-square small gain analysis approach, and obtain necessary and sufficient conditions for a system to be meansquare stabilizable via output feedback. For single-input, single-output(SISO) systems, the condition provides an analytical bound, demonstrating explicitly how plant unstable poles, nonminimum phase zeros, and time delay may impose a limit on the uncertainty variance required for mean-square stabilization. For MIMO minimum phase systems with possible delays, the condition amounts to solving a generalized eigenvalue problem, readily solvable using linear matrix inequality optimization techniques.     

Positive observer design for positive Markovian jump systems with partly known transition rates

The paper is concerned with positive observer design for positive Markovian jump systems with partly known transition rates. By applying a linear co-positive type Lyapunov-Krasovskii function, a sufficient condition is proposed to ensure the stochastic stability of the error positive system and the existence of the positive observer, which is computed in linear programming. Finally, an example is given to demonstrate the validity of the main results.     

Stochastic Optimal Control Problem in Advertising Model with Delay

This paper investigates the optimal control problem arising in advertising model with delay. The authors reformulate the problem in Hilbert space by stochastic evolution equation and consider the optimal control problem of controlled stochastic evolution system. The necessary and sufficient optimality conditions of the control are established. The proposed approach is different from most existing studies of optimal advertising policy problem with delay. These results are applied to the optimal advertising policy problem under two different structures and the optimal advertising strategies are obtained.     

THE CRITERIA OF ULTIMATE BOUNDEDNESS FOR NONAUTONOMOUS DIFFUSIVE LOTKA-VOLTERRA SYSTEMS IN TWO HETEROGENEOUS PATCHES

1 Introduction and PreliminariesSince the interrelations between the orgachms and the environment seem to be essentialto the system's stabilityll], the effect of diction on the possibility of species coechtence in anecological community has been an haportat subjeCt in population biology. EXcept for someexamples known as ~ive instability or diffusion-induced instability especially in aquaticsystems (see [2]), a diffusion process generally tends to promote stability in ecological systems.Numero…     

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.     

Research on robust mean square stability of networked control systems with packet dropout

This paper is concerned with the robust stabilization problem of networked control systems with stochastic packet dropouts and uncertain parameters. Considering the stochastic packet dropout occuring in two channels between the sensor and the controller, and between the controller and the actuator, networked control systems are modeled as the Markovian jump linear system with four operation modes. Based on this model, the necessary and sufficient conditions for the mean square stability of the deterministic...     

Long-Time Behavior and Density Function of a Stochastic Chemostat Model with Degenerate Diffusion

This paper considers a stochastic chemostat model with degenerate diffusion. Firstly, the Markov semigroup theory is used to establish sufficient criteria for the existence of a unique stable stationary distribution. The authors show that the densities of the distributions of the solutions can converge in L¹ to an invariant density. Then, conditions are obtained to guarantee the washout of the microorganism. Furthermore, through solving the corresponding Fokker-Planck equation, the authors give the exact expression of density function around the positive equilibrium of deterministic system. Finally, numerical simulations are performed to illustrate the theoretical results.

     

Stochastic maximum principle for optimal control problems of forward-backward delay systems involving impulse controls

This paper is concerned with the optimal control problems of forward-backward delay systems involving impulse controls. The authors establish a stochastic maximum principle for this kind of systems. The most distinguishing features of the proposed problem are that the control variables consist of regular and impulsive controls, both with time delay, and that the domain of regular control is not necessarily convex. The authors obtain the necessary and sufficient conditions for optimal controls, which have potential applications in mathematical finance.     

Moment Equations of Linear It Stochastic Systems with Applications

1.INTRODUCTIONAsiswellknown,stochasticsystemmodeloftheIt6typeisoneofthemostimportantmodelsforstochasticsystems,manystochasticsystemswithcolorednoisecanbestudiedwithhelpoftheIt6stochasticsystems[if.ForthestabilityandcontrolproblemofIt6stochasticsystems,nlallyresultshavebeenobtainedintheliteratures[l~6].Whilesomebasicproblems,suchasthenecessaryandsufficientconditionofmean-squarestabilityoflinearIt6stochasticsystems,havehotbeensolved.Inthepreviousliterature,someresultsonthestabilityoflinear…     

EXISTENCE AND UNIQUENESS AND STABILITY OF SOLUTIONS FOR STOCHASTIC IMPULSIVE SYSTEMS

This paper studies the existence, uniqueness, and stability of solutions for stochastic impulsive systems. By employing Lyapunov-like functions, some sufficient conditions of the global existence, uniqueness, and stability of solutions for stochastic impulsive systems are established. Furthermore, the results are specialized to the case of linear stochastic impulsive systems. Finally, some examples are given to illustrate the applications of our theory.     

离散时间随机系统的稳定性分析

对由定常非线性随机差分模型所定义状态空间为一般可测空间的离散时间随机系统，本文应用一般状态马氏链遍历性有关理论分析了系统的稳定性问题，给出了由系统相应确定性部分的Ｌｙａｐｕｎｏｖ函数来判别系统稳定的若干充分条件。     

Finite-time stability and stabilization of Markovian switching stochastic systems with impulsive effects

Many practical systems in physics,biology,engineering and information science exhibit impulsive dynamical behaviors due to abrupt changes at certain instants during the dynamical processes.The problems of finite-time stability analysis are investigated for a class of Markovian switching stochastic systems,in which exist impulses at the switching instants.Multiple Lyapunov techniques are used to derive sufficient conditions for finite-time stochastic stability of the overall system.Furthermore,a state feedback controller,which stabilizes the closed loop systems in the finite-time sense,is then addressed.Moreover,the controller appears not only in the shift part but also in the diffusion part of the underlying stochastic subsystem.The results are reduced to feasibility problems involving linear matrix inequalities (LMIs).A numerical example is presented to illustrate the proposed methodology.     

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.     

STABILITY OF SWITCHED POLYNOMIAL SYSTEMS

This paper investigates the stability of （switched） polynomial systems. Using semi-tensor product of matrices, the paper develops two tools for testing the stability of a （switched） polynomial system. One is to convert a product of multi-variable polynomials into a canonical form, and the other is an easily verifiable sufficient condition to justify whether a multi-variable polynomial is positive definite. Using these two tools, the authors construct a polynomial function as a candidate Lyapunov function and via testing its derivative the authors provide some sufficient conditions for the global stability of polynomial systems.     

The sufficient and necessary condition of the major stochastic preference rule in group decision making

Group decision making problem with stochastic preference is investigated.The authors present four rational conditions for testing group stochastic preference rule,and prove that the combination of these four rational conditions is the sufficient and necessary condition of major stochastic preference rule for group stochastic preference rule.     

Maximum Principle of Optimal Stochastic Control with Terminal State Constraint and Its Application in Finance

This paper considers the optimal control problem for a general stochastic system with general terminal state constraint. Both the drift and the diffusion coefficients can contain the control variable and the state constraint here is of non-functional type. The author puts forward two ways to understand the target set and the variation set. Then under two kinds of finite-codimensional conditions, the stochastic maximum principles are established, respectively. The main results are proved in two different ways. For the former, separating hyperplane method is used; for the latter, Ekeland’s variational principle is applied. At last, the author takes the mean-variance portfolio selection with the box-constraint on strategies as an example to show the application in finance.     

Properties of storage functions and applications to nonlinear stochastic <Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> control

This paper discusses the properties of the storage functions for a class of nonlinear stochastic systems. Some necessary and sufficient conditions for a function to be a storage function are derived. As applications, the finite and infinite horizon nonlinear stochastic H _∞ controls for systems with state, control, and external disturbance dependent noise are investigated, which generalize the previous results.     

线性不确定随机系统时滞相关的H∞滤波

研究了一类带有时变状态时滞和参数不确定性的连续时间线性随机系统的鲁棒H_∞滤波问题。目的是设计一个线性滤波器使滤波误差动态系统是指数均方稳定的,并满足给定的H_∞性能指标。应用描述符系统模型转换,建立了新的Lyapunov-Krasovskii 函数。通过引入自由加权矩阵,消除了Lyapunov矩阵和系统矩阵的乘积项,从而无需在滤波器设计过程中对Lyapunov矩阵作任何约束,这在很大程度上降低了滤波器设计的保守性。基于LMI方法,针对精确已知随机系统和带有结构不确定性的随机系统,分别提出了时滞相关的鲁棒H_∞滤波器存在的充分性条件。仿真结果表明所提出的设计方法是有效的。     

H∞ control for stochastic systems with time-delay

The H∞-control problem of stochastic systems with time-delay is considered. The sufficient conditions are obtained, under which there are always state-feedback control and dynamic output-feedback control so that the resulting closed-loop system is internaly stable and L2 input-output stable in the sense of expectation. Furthermore, the explicit formulas of both kinds of controls are derived. An example is included to illustrate the correctness of theoretic results.