Fault detection filter design for linear discrete time-varying systems with multiplicative noise

The problem of fault detection for linear discrete timevarying systems with multiplicative noise is dealt with.By using an observer-based robust fault detection filter(FDF) as a residual generator,the design of the FDF is formulated in the framework of H ∞ filtering for a class of stochastic time-varying systems.A sufficient condition for the existence of the FDF is derived in terms of a Riccati equation.The determination of the parameter matrices of the filter is converted into a quadratic optimization problem,and an analytical solution of the parameter matrices is obtained by solving the Riccati equation.Numerical examples are given to illustrate the effectiveness of the proposed method.     

Observer-based controller design for singular stochastic Markov jump systems with state dependent noise

This paper is concerned with the problem of observer-based controller design for singular stochastic Markov jump systems with state-dependent noise. Two concepts called “non-impulsiveness” and “mean square admissibility” are introduced, which are different from previous ones. Sufficient conditions for the open- and closed-loop singular stochastic Markov jump systems with state-dependent noise to be mean square admissible are provided in terms of strict LMIs. The controller gain and the observer gain which guarantee the resulting closed-loop error system to be mean square admissible are obtained in turn by solving the strict LMIs. A numerical example is presented to show the efficiency of the design approach.     

分数阶线性系统的能观性研究

在对一类由分数阶线性微分方程描述的系统的能观性问题研究中,通过分数阶线性定常系统求解,给出了分数阶线性定常和时变系统一般解的统一表达式。在给出分数阶系统能观性定义的基础上,提出并证明了分数阶线性系统时变和定常系统能观性的充分和必要条件,以及分数阶线性定常系统的能观性判据,所得结论对分数阶控制系统的分析与综合是有益的。     

基于观测器的不确定时滞Markov跳变系统H∞控制

讨论了一类线性不确定时滞Markov跳变系统的控制问题,针对能量有界的输入噪声,设计了基于观测器的优化鲁棒H∞控制器。基于鲁棒控制理论,通过对重构的观测器系统的分析,提出了使得系统随机稳定且满足一定输入输出H∞增益的模态依赖的控制器存在条件。结合构造的Lyapunov函数和线性矩阵不等式变换,给出了H∞控制器的设计方法,并将其描述为一个优化问题。基于观测器设计的优化H∞控制器使系统具有随机稳定性,状态的跟踪性能好,抑制干扰能力强,满足所给的范数指标。仿真示例说明了设计方法的有效性。     

The maximum principle for partially observed optimal control of forward-backward stochastic systems with random jumps

This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.     

On optimal mean-field control problem of mean-field forward-backward stochastic system with jumps under partial information

This paper considers the problem of partially observed optimal control for forward-backward stochastic systems driven by Brownian motions and an independent Poisson random measure with a feature that the cost functional is of mean-field type. When the coefficients of the system and the objective performance functionals are allowed to be random, possibly non-Markovian, Malliavin calculus is employed to derive a maximum principle for the optimal control of such a system where the adjoint process is explicitly expressed. The authors also investigate the mean-field type optimal control problem for the system driven by mean-field type forward-backward stochastic differential equations (FBSDEs in short) with jumps, where the coefficients contain not only the state process but also its expectation under partially observed information. The maximum principle is established using convex variational technique. An example is given to illustrate the obtained results.     

Controlled mean-field backward stochastic differential equations with jumps involving the value function

This paper discusses mean-field backward stochastic differential equations (mean-field BSDEs) with jumps and a new type of controlled mean-field BSDEs with jumps, namely mean-field BSDEs with jumps strongly coupled with the value function of the associated control problem. The authors first prove the existence and the uniqueness as well as a comparison theorem for the above two types of BSDEs. For this the authors use an approximation method. Then, with the help of the notion of stochastic backward semigroups introduced by Peng in 1997, the authors get the dynamic programming principle (DPP) for the value functions. Furthermore, the authors prove that the value function is a viscosity solution of the associated nonlocal Hamilton-Jacobi-Bellman (HJB) integro-partial differential equation, which is unique in an adequate space of continuous functions introduced by Barles, et al. in 1997.     

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).     

Maximum principle for forward-backward stochastic control system with random jumps and applications to finance

<正> Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both diffusion and jump coefficients.The result is applied to a mean-varianceportfolio selection mixed with a recursive utility functional optimization problem.Explicit expressionof the optimal portfolio selection strategy is obtained in the state feedback form.     

On passivity of state delayed stochastic jump systems

1.INTRODUCTION Stochasticjumpsystemisaspecialkindofhybridsys tems.Itisdescribedbyacontinuous timefinite state Markovprocesswhichreferstothemode,andbya dynamicsystemofdifferentialequationswhichrefers tothestate.Thejumpsystemscanmodelthedynam icsystemssubjecttoabruptvariationintheirstruc turesandthereforattractresearchinterestinginthe world.Recently,thereweresomeresearchesoncon trolproblemsforjumpsystemswithtimedelay[1,2].Passivityplaysanimportantroleinsystemand controltheory.Butalmostallr…     

On formability of linear continuous-time multi-agent systems

This paper is focused on formability of multi-agent systems(MASs).The problem is concerned with the existence of a protocol that has the ability to drive the MAS involved to the desired formation,and thus,is of essential importance in designing formation protocols.Formability of an MAS depends on several key factors:agents’ dynamic structures,connectivity topology,properties of the desired formation and the admissible control set.Agents of the MASs considered here are described by a general continuous linear time-invariant(LTI) model.By using the matrix analysis and algebraic graph theory,some necessary and sufficient conditions on formability of LTI-MASs are obtained.These conditions characterize in some sense the relationship of formability,connectivity topology,formation properties and agent dynamics with respect to some typical and widely used admissible protocol sets.     

Impulse observability and impulse controllability of regular degenerate evolution systems

Impulse observability and impulse controllability of regular degenerate evolution systems are discussed by using functional analysis and operator theory in Banach space. Necessary and sufficient conditions for the impulse observability and impulse controllability of the system are obtained. This research is theoretically important for studying the design of the degenerate evolution system.     

时滞随机线性大系统的指数稳定性

针对一般随机线性时滞微分方程，给出了方程的平凡解的几乎必然指数稳定性的一个充分条件，由此利用时滞随机系统的比较原理建立一般时滞随机线性大系统的二阶矩指数稳定与几乎必然指数稳定新的代数判据．利用恰当的Lyapunov函数结合不等式技巧得到了这些条件．特别是用一个代数方程给出了依赖时滞的Lyapunov指数的估计．并用实例加以验证．     

On controllability for stochastic control systems when the coefficient is time-variant

<正> This paper investigates the controllability problem of time-variant linear stochastic controlsystems.A sufficient and necessary condition is established for stochastic exact controllability,whichprovides a useful algebraic criterion for stochastic control systems.Furthermore,when the stochasticsystems degenerate to deterministic systems,the algebraic criterion becomes the counterpart for thecomplete controllability of deterministic control systems.     

Admissible model noise upper bound with constraint of stochastic passage characteristics

In some object tracking systems,the moving object future position is an area (i.e.,target area).It is a successful estimation strategy if the predicted points fall in the target area.If the object makes a sudden maneuvering,the prediction may get out of the target area easily which may make the tracking system lose the object.The aim is to investigate the admissible maximum object maneuvering intensity,which is characterized as model noise variance,for such kind of tracking system.Firstly,the concept of stochastic passage characteristics over the boundary of target area and their relationship with prediction error variance are described.Secondly,the consistency among the indices of regional pole,prediction error variance and stochastic passage characteristics is analyzed.Thirdly,the multi-indices constraints are characterized by a set of bi-linear matrix inequalities (BMIs).Then,the admissible maximum model noise variance and the satisfactory estimation strategy are presented by iteratively solving linear matrix inequalities (LMIs) to approximate BMIs.Finally,a numerical example is proposed to demonstrate the obtained results.     

随机可变时滞系统的渐近稳定性

讨论了一类随机可变时滞系统解的渐近稳定性。应用It 公式、半鞅收敛定理与多个Lyapunov函数建立了这类随机可变时滞系统渐近稳定性的有效判据,使实际应用中构造Lyapunov函数更为方便。同时也说明了结果包含经典的随机系统稳定性结果为其特殊情况。与经典的随机稳定性理论相比,所建立的稳定性结果无须LV负定,充分利用了随机扰动项的作用,并且从理论上解释了一个不稳定的系统有时加入适当随机扰动后反而稳定。最后,举例说明了结果的有效性     

Robust reliable H∞ control for discrete-time Markov jump linear systems with actuator failures

The robust reliable H∞ control problem for discrete-time Markovian jump systems with actuator failures is studied. A more practical model of actuator failures than outage is considered. Based on the state feedback method, the resulting closed-loop systems are reliable in that they remain robust stochastically stable and satisfy a certain level of H∞ disturbance attenuation not only when all actuators are operational, but also in case of some actuator failures, The solvability condition of controllers can be equivalent to a feasibility problem of coupled linear matrix inequalities （LMIs）. A numerical example is also given to illustrate the design procedures and their effectiveness.     

On the observability of free Boolean networks via the semi-tensor product method

This paper investigates the observabihty of free Boolean networks by using the semi-tensor product method,and presents some new results.First,the concept of observability for free Boolean networks is proposed,based on which and the algebraic form of Boolean networks,a kind of observabihty matrix is constructed.Second,by the observability matrix,a new necessary and sufficient condition is given for the observability of Boolean networks.Third,the concept of observabihty index for observable Boolean networks is defined,and an algorithm is established to calculate the observability index.Finally,a practical example of D.Melanogaster segmentation polarity gene networks is studied to support our new results.The study of the illustrative example shows that the new results obtained in this paper are very effective in investigating the observability of free Boolean networks.     

Stabilization of switched linear systems with constrained inputs

The stabilization of switched linear systems with constrained inputs(SLSCI) is considered. The authors design admissible linear state feedbacks and the switching rule which has a minimal dwell time(MDT) to stabilized the system.First,for each subsystem with constrained inputs,a stabilizing linear state feedback and an invariant set of the closed-loop system are simultaneously constructed, such that the input constraints are satisfied if and only if the closed-loop system’s states lie inside this set.Then,by constructing a quadratic Lyapunov function for each closed-loop subsystem,an MDT is deduced and an MDT-based switching strategy is presented to ensure the stability of the switched system.