Almost sure estimation and synthesis of ultimate bounds for discrete-time Markov jump linear systems

This paper is concerned with the problems of almost sure ultimate bound estimation and controller design for Markov jump linear systems with bounded stochastic disturbances. By utilising a Lyapunov-based scheme proposed in this paper, an almost sure estimation of ellipsoidal ultimate bound (EUB) of the system is obtained through tractable matrix inequalities. On the basis of the estimation results, the problem of designing mode-dependent state feedback controllers that make the closed-loop system admit a prescribed ellipsoid as an EUB is considered. The obtained results on estimation and synthesis are then extended to the case of systems with deficient mode information. Finally, a practical example in DC motor devices is presented to demonstrate the applicability of the obtained results.     

具有脉冲效应的切换随机系统的几乎必然稳定性

针对一类在切换时刻具有脉冲行为的Markov切换非线性随机系统,首先,应用切换的Lyapunov函数方法研究系统的稳定性,给出系统几乎必然稳定的充分条件,该条件不依赖于系统的矩稳定性;然后,进一步对线性系统的稳定化问题进行分析与设计,对随机子系统的控制结构同时出现在方程的位移部分与扩散部分,给出相应的状态反馈增益矩阵的求解方法;最后,数值算例说明了所设计方法的有效性.     

Almost sure exponential stabilisation of stochastic systems by state-feedback control

So far, a major part of the literature on the stabilisation issues of stochastic systems has been dedicated to mean-square stability. This paper develops a new class of criteria for designing a controller to stabilise a stochastic system almost surely which is unable to be stabilised in mean-square sense. The results are expressed in terms of linear matrix inequalities (LMIs) which are easy to be checked in practice by using MATLAB Toolbox. Moreover, the control structure in this paper appears not only in the drift part but also in the diffusion part of the underlying stochastic system.     

具有干扰的马尔科夫跳跃线性系统几乎处处稳定性充分条件

跳跃线性系统是一类具有随机跳变参数的线性系统,其跳变参数根据给定的有限状态马尔科夫链演化,这样的模型可以用来描述出现故障或者在结构卜突然发生变化的系统.本文采用随机李雅谱诺夫第二方法研究了具有干扰的离散时间跳跃线性系统的几乎处处稳定性,得到了一类充分条件.并由此条件进一步得出了更易于检测其几乎处处稳定性的允分条件.     

On almost sure stability of continuous-time Markov jump linear systems

In this paper, we study the almost sure stability of continuous-time jump linear systems with a finite-state Markov form process. A sufficient condition for almost sure stability is derived that refers to the statistics of the transition matrix over m switches. It is shown that, if the system is exponentially almost sure stable, there exists a finite m such that the criterion is satisfied. In order to evaluate the expected value appearing in the condition, an efficient Monte Carlo algorithm is worked out.     

Almost sure exponential stability of neutral stochastic delayed cellular neural networks

In this paper, almost sure exponential stability of neutral delayed cellular neural networks which are in the noised environment is studied by decomposing the state space to sub-regions in view of the saturation linearity of output functions of neurons of the cellular neural networks. Some algebraic criteria are obtained and easily verified. Some examples are given to illustrate the correctness of the results obtained.     

Almost sure exponential stability of neutral stochastic delayed cellular neural networks

In this paper, almost sure exponential stability of neutral delayed cellular neural networks which are in the noised environment is studied by decomposing the state space to sub-regions in view of the saturation linearity of output functions of neurons of the cellular neural networks. Some algebraic criteria are obtained and easily verified. Some examples are given to illustrate the correctness of the results obtained.     

Conditions for local almost sure asymptotic stability

In this paper, we investigate local asymptotic stability ensured by the addition of Gaussian white noise into dynamical systems. There are different stability notions for stochastic systems, such as asymptotic stability in probability (ASiP) and uniform almost sure asymptotic stability (UASAS). The local ASiP property is incapable of ensuring that sample paths converge to the origin with probability one, whereas the local UASAS property is capable of it. However, in general, the local UASAS property requires tight conditions. Here, we provide our notion of local almost sure asymptotic stability (local ASAS) to relax the conditions with both almost sure convergence of sample paths to the origin and the existence of bounded (weak) invariant sets. We find that the addition of Gaussian white noise always prevents the origin from being locally UASAS as long as we consider smooth Lyapunov functions; however, it is possible to make the origin locally ASAS. The result is confirmed by a simple example of elimination of unstable equilibria by deliberately adding Gaussian white noise.     

Moment stability for linear systems with a random parametric excitation

Moment stability for linear systems with a nonwhite parametric noise is considered. A method of reduction of the study of this stability to the study of stability for large-scale matrices is proposed. Mean square stability diagrams for random harmonic oscillator are presented.     

Periodically switched stability induces exponential stability of discrete-time linear switched systems in the sense of Markovian probabilities

The conjecture that periodically switched stability implies absolute asymptotic stability of random infinite products of a finite set of square matrices, has recently been disproved under the guise of the finiteness conjecture. In this paper, we show that this conjecture holds in terms of Markovian probabilities. More specifically, let S_k∈C^n×n,1≤k≤K, be arbitrarily given K matrices and , where n,K≥2. Then we study the exponential stability of the following discrete-time switched dynamics S: where can be an arbitrary switching sequence.For a probability row-vector and an irreducible Markov transition matrix with , we denote by the Markovian probability on corresponding to . By using symbolic dynamics and ergodic-theoretic approaches, we show that, if S possesses the periodically switched stability then, (i) it is exponentially stable -almost surely; (ii) the set of stable switching sequences has the same Hausdorff dimension as . Thus, the periodically switched stability of a discrete-time linear switched dynamics implies that the system is exponentially stable for “almost” all switching sequences.     

Transition probability bounds for the stochastic stability robustness of continuous- and discrete-time Markovian jump linear systems

This paper considers the robustness of stochastic stability of Markovian jump linear systems in continuous- and discrete-time with respect to their transition rates and probabilities, respectively. The continuous-time (discrete-time) system is described via a continuous-valued state vector and a discrete-valued mode which varies according to a Markov process (chain). By using stochastic Lyapunov function approach and Kronecker product transformation techniques, sufficient conditions are obtained for the robust stochastic stability of the underlying systems, which are in terms of upper bounds on the perturbed transition rates and probabilities. Analytical expressions are derived for scalar systems, which are straightforward to use. Numerical examples are presented to show the potential of the proposed techniques.     

Almost sure exponential stability of stochastic fluid networks with nonlinear control

Due to the objective of controlling fluid flows, fluid networks are high-order nonlinear stochastic systems in essential. Taking the nonlinearities in pressure drop of fan branch, measurement error of inertia coefficients, and random factors into consideration, this paper presents a stochastic fluid networks model described by Itô stochastic differential equations. As drift term of the stochastic fluid networks does not satisfy the linear growth condition, the almost sure exponential stability cannot get from the moment exponential stability. We directly investigate the almost sure exponential stability of the tracking and regulation problems for fluid networks under decentralised and adaptive control. It shows that the fluid flows in all branches can reach their reference values if we set controller only in links of the networks. We illustrate the results with two examples.     

On the stability of slowly time-varying linear systems

New conditions are given in both deterministic and stochastic settings for the stability of the system x=A(t)x when A(t) is slowly varying. Roughly speaking, the eigenvalues of A(t) are allowed to wander into the right half-plane as long as on average they are strictly in the left half-plane.This work was funded by the NSF under Grant ECS-8806063, and was completed while the author was with the Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, U.S.A.     

Almost sure limit theorems for the maxima of some strongly dependent Gaussian sequences

We proved some almost sure limit theorems for standard strongly dependent Gaussian sequences in nonstationary cases under some mild conditions.     

Delay-dependent stability analysis for Markovian jump systems with interval time-varying-delays

This paper proposes improved stochastic stability conditions for Markovian jump systems with interval time-varying delays. In terms of linear matrix inequalities (LMIs), less conservative delay-range-dependent stability conditions for Markovian jump systems are proposed by constructing a different Lyapunov-Krasovskii function. The resulting criteria have advantages over some previous ones in that they involve fewer matrix variables but have less conservatism. Numerical examples are provided to demonstrate the efficiency and reduced conservatism of the results in this paper.     

Robust sampled-data control for Markovian jump linear systems

In this paper, we consider the problem of robust control for uncertain sampled-data systems that possess random jumping parameters which is described by a finite-state Markov process. The conditions for the existence of a stabilizing control and optimal control for the underlying systems are obtained. The desired controllers are designed which are in terms of matrix inequalities. Finally, a numerical example is given to show the potential of the proposed techniques.     

Almost sure and mean square exponential stability of numerical solutions for neutral stochastic functional differential equations

In this paper, we investigate the almost sure and mean square exponential stability of the Euler method and the backward Euler method for neutral stochastic functional differential equations (NSFDEs). Moreover, the almost sure and pth moment exponential stability of exact solutions for NSFDEs are considered. It is shown that the Euler method and the backward Euler method can reproduce the property of almost sure and mean square exponential stability of exact solutions to NSFDEs under suitable conditions. Numerical examples are demonstrated to illustrate the effectiveness of our theoretical results.     

Almost sure convergence rates for system identification using binary,quantized, and regular sensors

This paper presents almost sure convergence rates for system identification under binary, quantized, and regular sensors. To accommodate practical model complexity constraints, the system under consideration is represented by a modeled part together with an unknown-but-bounded unmodeled dynamics. Under uncorrelated noise sequences, identification errors with different sensor types are studied and tight error bounds are obtained without information or constraints on noise moment conditions. The results are then extended to correlated noise sequences whose remote past and distant future are asymptotically independent. In both cases, almost sure error bounds of the laws of iterated logarithms type are derived.     

The almost sure asymptotic stability and pth moment asymptotic stability of nonlinear stochastic delay differential systems with polynomial growth

In this paper, we discuss the asymptotic stability of nonlinear stochastic delay differential systems (SDDSs) whose coefficients obey the polynomial growth condition. By applying some novel techniques, we establish some easily verifiable conditions under which such SDDSs are almost surely asymptotically stable and pth moment asymptotically stable. A nontrivial example is provided to illustrate the effectiveness of our results. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society