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The semi-Markov jump linear system is more general than the classic Markov jump linear system. In the semi-Markov jump linear systems, the governing stochastic process is not a Markov process, but a semi-Markov process. Instead of the exponential distribution for the sojourn-time in each mode in the jump linear system, the Weibull distribution is considered in this paper. By deriving the infinitesimal...
Peer to peer file exchange systems such as BitTorrent are changing the way in which content is distributed in the Internet. Service capacity for a certain content adjusts dynamically as a function of peer population, thus achieving scalability. This dynamic behavior has been the subject of recent analytical studies. In this paper, we propose a partial differential equation model for BitTorrent-like...
We develop a multi-input, multi-output direct adaptive controller for discrete-time, possibly nonminimum-phase, systems with unknown nonminimum-phase zeros. The adaptive controller requires limited modeling information about the system, specifically, Markov parameters from the control input to the performance variables. Often, only a single Markov parameter is required, even in the nonminimum-phase...
This paper introduces the class of dual-random-rate systems (i.e., dual-rate systems with random output rates), which is well suited to model image-based control systems. It is shown that a dual-random-rate system can be reformulated as a switched linear system with a (quasi-periodic) random switching signal that is a static function of Markov chain. This reformulation makes it possible to study dual-random-rate...
Almost sure asymptotic stabilization problem of continuous-time switched linear stochastic dynamical systems is considered. The mode signal, which manages the transition between subsystems, is modeled as a Markov chain. Mode information is assumed to be only available at certain time instances. We propose a control law that depends on the sampled information of the mode signal, which is constructed...
The problem of mean square stabilization of a discrete-time linear dynamical system over a Markov time-varying digital feedback channel is studied. In the scalar case, it is shown that the system can be stabilized if and only if a Markov jump linear system describing the evolution of the estimation error at the decoder is stable — videlicet if and only if the product of the unstable mode of the system...
This paper considers games with incomplete asymmetric information, where one player (the deceiver) has privileged information about the other (the mark) and intends to employ it for belief manipulation. We use hypergames to represent the asymmetric information available to players and assume a probabilistic model for the actions of the mark. This framework allows us to formalize various notions of...
Quantization effects are inevitable in networked control systems (NCSs). These quantization effects can be reduced by increasing the number of quantization levels. However, increasing the number of quantization levels may lead to network congestion, (i.e., the network needs to transfer more information than its capacity). In this paper, we investigate the problem of designing a robust ℋ∞ output feedback...
The stability of a class of Markov jump linear systems (MJLS) characterized by constant transition rates and piecewise-constant system dynamics is investigated. For these Switching Dynamics Markov jump linear systems (SD-MJLS), almost sure exponential stability (ASE-stability) is analyzed by applying the ergodic law of large numbers under the assumption that suitable average contractivity conditions...
This paper focuses on analyzing the interactions emerging between users in online communities. Network utility maximization and other methods are not effective when the communities are composed of intelligent and self-interested users (multimedia social communities, social networks etc.), because the interests of the individual users may be in conflict. In our prior work, we propose to design protocols...
This paper studies Mean square stability, Stochastic stability and Exponential stability for discrete-time singular linear systems whose parameters are driven by a finite state Markov chain. It is shown the equivalence of these notions under certain conditions. New necessary conditions for mean square stability in terms of generalized Lyapunov equations for homogeneous and non-homogeneous of this...
This paper deals with the mode-dependent static output feedback stabilization problem of linear networked control systems (NCSs) with the effect of the network-induced time delays. The overall delays induced by communication channel are modeled as a Markov chain which is believed to be an ideal model of random time delay. The resulting closed-loop system is transformed to a Markovian jump linear system...
This paper presents an H∞ controller design method for a class of Networked Control Systems (NCSs) with bounded packet dropouts. The state feedback closed-loop NCS is modeled as a Markov system. A sufficient condition for stochastic stability with an H∞ disturbance attenuation level is derived through a Lyapunov function, which is dependent on the upper bound of the number of consecutive packet dropouts...
This paper considers iterative learning control for the practically relevant case of deterministic discrete linear plants where the first Markov parameter is zero. A 2D systems approach that uses a strong form of stability for linear repetitive processes is used to develop a one step control law design for both trial-to-trial error convergence and along the trial performance. The resulting design...
We present an algorithm that, given any target tree, synthesizes reversible self-assembly rules that provide a maximum yield in the sense of stochastic stability. If the reversibility constraint is relaxed then the same algorithm can be trivially modified so that it converges to a maximum yield almost surely. The proof of correctness in both cases relies on the notion of a completing rule. We examine...
The applications of dynamic content updates for a group of users, for example weather report and traffic congestion broadcast, have been shown to benefit significantly from Delay Tolerant Networks (DTN) communication mechanisms such as opportunistic contact and user sharing. In this paper, we study the dynamic content updates over energy-constrained DTN, and focus on its asymptotic properties about...
In this paper, we consider the design of access schemes for secondary users in cognitive radio systems based on the primary user feedback information. We consider a secondary user employing a random access scheme with an access probability that depends on the primary user feedback state. We show that the proposed scheme can enhance the system performance in terms of the secondary throughput and/or...
Congestion control for wireless networks is much more challenging than that for wired networks, due to the limited wireless spectrum and severe impairments of wireless medium which suffer time-varying fading, shadowing, interference, etc. Although the stability of the Internet using TCP congestion control and active queue management (AQM) schemes has been extensively investigated, effective congestion...
Quantizers with coarser quantization densities are helpful in reducing network congestion. In this paper, we investigate the problem of designing a robust H∞ output feedback controller for discrete-time networked systems with an adaptive quantization density or limited information. A Markov process is used to model the randomness of the network load condition and a Bernoulli process is used to model...
Towards the MAC design of the dynamic sharing spectrum communication system, this paper proposed a new MAC frame structure which can be used in centralized networks. And design a Slotted ALOHA access control algorithm based the feedback competition CSI (channel state information) of access users. Then through analyzing the delay features and the stability, we propose a new MFpBA to assure the system...
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