Distributed clock skew and offset estimation from relative measurements in mobile networks with Markovian switching topology

We analyze a distributed algorithm for the estimation of scalar parameters belonging to nodes in a mobile network from noisy relative measurements. The motivation comes from the problem of clock skew and offset estimation for the purpose of time synchronization. The time variation of the network was modeled as a Markov chain. The estimates are shown to be mean square convergent under fairly weak assumptions on the Markov chain, as long as the union of the graphs is connected. Expressions for the asymptotic mean and correlation are also provided.     

Robust decentralized stabilization of Markovian jump large-scale systems: A neighboring mode dependent control approach

This paper is concerned with the decentralized stabilization problem for a class of uncertain large-scale systems with Markovian jump parameters. The controllers use local subsystem states and neighboring mode information to generate local control inputs. A sufficient condition involving rank constrained linear matrix inequalities is proposed for the design of such controllers. A numerical example is given to illustrate the developed theory.     

Optimal time-weighted H 2 model reduction for Markovian jump systems

This article addresses the optimal time-weighted H ₂ model reduction problem for Markovian jump linear systems. That is, for a given mean square stable Markovian jump system, our aim is to find a mean square stable jump system of lower order such that the time-weighted H ₂ norm of the corresponding error system is minimised. The time-weighted H ₂ norm of the system is first defined, and then a computational method is constructed. The computation requires the solution of two sets of recursive Lyapunov-type linear matrix equations associated with the Markovian jump system. To solve the optimal time-weighted H ₂ model reduction problem, we propose a gradient flow method for its solution. A necessary condition for minimality is derived, and a computational procedure is provided to obtain the minimising reduced-order model. The necessary condition generalises the standard result for systems when Markov jumps and the time-weighting term do not appear. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed approach.     

马氏环境中一般生灭链的灭绝概率及平均吸收时间的计算

将马氏环境中的生灭链 (GBDME)灭绝概率及平均吸收时间的计算 ,推广到马氏环境中一般生灭链 (GB DME) ,得到了关于灭绝概率及平均吸收时间的向量差分方程 .     

Simultaneous ℋ︁2/ℋ︁∞ control of uncertain jump systems with functional time‐delays

This paper presents new results pertaining to the control design of a class of linear uncertain systems with Markovian jump parameters. An integral part of the system dynamics is a delayed state in which the time‐delays are mode dependent. The jumping parameters are modelled as a continuous‐time, discrete‐state Markov process and the uncertainties are norm‐bounded. We construct an appropriate Lyapunov–Krasovskii functional and design a simultaneous ℋ︁₂/ℋ︁_∞ controller which minimizes a quadratic ℋ︁₂ performance measure while satisfying a prescribed ℋ︁_∞‐norm bound on the closed‐loop system. It is established that sufficient conditions for the existence of the simultaneous ℋ︁₂/ℋ︁_∞ controller and the associated performance upper bound are cast in the form of linear matrix inequalities. Simulation results are provided and extension to the case where the jumping rates are subject to uncertainties is presented. Copyright © 2007 John Wiley & Sons, Ltd.     

A binomial approximation of lot yield under Markov modulated Bernoulli item yield

The existing literature that models item-by-item production yield as a Bernoulli process assumes that the intraperiod likelihood of producing an acceptable item is stationary. We investigate the stochastic process that results from relaxing this assumption to account for system deterioration during each production run. More specifically, we consider a Bernoulli yield model with a non-stationary parameter that depends on the deterioration level of the system, which evolves according to a discrete-time Markov chain. For tractability reasons, we construct a simple binomial approximation of the non-stationary process, and compare the two yield distributions both analytically and numerically. Our results suggest that the approximation performs well, even when the deterioration occurs relatively fast, which serves to validate existing (and future) decision models that impose the stationarity assumption.     

Stabilization of discrete-time Markovian jump linear systems via time-delayed and impulsive controllers

This paper discusses the stabilization problem for a class of discrete-time Markovian jump linear systems with time-delayed and impulsive controllers. The delay in the mode signal is assumed to be constant, while that in the system state may be time-varying. First, a hybrid controller with delay and impulses is introduced for the discrete-time stochastic systems. Then, some sufficient conditions are proposed for the design of a hybrid controller such that the closed-loop system is stochastically stable. Finally, a numerical example is provided to illustrate the effectiveness of the proposed result.     

Loss behavior in space priority queue with batch Markovian arrival process — discrete-time case

This paper applies matrix-analytic approach to the examination of the loss behavior of a space priority queue. In addition to the evaluation of the long-term high-priority and low-priority packet loss probabilities, we examine the bursty nature of packet losses by means of conditional statistics with respect to critical and non-critical periods that occur in an alternating manner. The critical period corresponds to having more than a certain number of packets in the buffer; non-critical corresponds to the opposite. Hence there is a threshold buffer level that splits the state space into two. By such a state-space decomposition, two hypothesized Markov chains are devised to describe the alternating renewal process. The distributions of various absorbing times in the two hypothesized Markov chains are derived to compute the average durations of the two periods and the conditional high-priority packet loss probability encountered during a critical period. These performance measures greatly assist the space priority mechanism for determining a proper threshold. The overall complexity of computing these performance measures is of the order O(K²m₁³m₂³), where K is the buffer capacity, and m₁ and m₂ are the numbers of phases of the underlying Markovian structures for the high-priority and low-priority packet arrival processes, respectively. Thus the results obtained are computationally tractable and numerical results show that, by choosing a proper threshold, a space priority queue not only can maintain the quality of service for the high-priority traffic but also can provide the near-optimum utilization of the capacity for the low-priority traffic.