The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Jia You - One of the best experts on this subject based on the ideXlab platform.
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h filtering for sampled data stochastic systems with Limited Capacity channel
Signal Processing, 2011Co-Authors: Ming Liu, Jia YouAbstract:This paper investigates the H"~ filtering problem for sampled-data stochastic systems with Limited Capacity channel. The considered plant is described by a class of Ito stochastic systems subject to external disturbance. The output measurements are sampled and quantized, and then transmitted through a network medium. The aim of this paper is focused on the design of full order filters by using the quantized sampled outputs. In sampled-data systems, the value of the sampled signal increases abruptly at sampling times, and traditional filter design results based on time-independent Lyapunov-Krasovskii functionals (or Lyapunov-Razumikhin functions) may be conservative. The main contribution of this paper is to propose a new type of time-dependent Lyapunov function for Ito stochastic systems which does not increase in sampling times due to its special mathematical structure. Based on this approach, sufficient conditions for the existence of the proposed filter are established such that the filtering error system is stochastically stable and preserves a guaranteed H"~ performance. A numerical example is provided to illustrate the effectiveness of the proposed filtering technique in this paper.
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H∞ filtering for sampled-data stochastic systems with Limited Capacity channel
Signal Processing, 2011Co-Authors: Ming Liu, Jia YouAbstract:This paper investigates the H"~ filtering problem for sampled-data stochastic systems with Limited Capacity channel. The considered plant is described by a class of Ito stochastic systems subject to external disturbance. The output measurements are sampled and quantized, and then transmitted through a network medium. The aim of this paper is focused on the design of full order filters by using the quantized sampled outputs. In sampled-data systems, the value of the sampled signal increases abruptly at sampling times, and traditional filter design results based on time-independent Lyapunov-Krasovskii functionals (or Lyapunov-Razumikhin functions) may be conservative. The main contribution of this paper is to propose a new type of time-dependent Lyapunov function for Ito stochastic systems which does not increase in sampling times due to its special mathematical structure. Based on this approach, sufficient conditions for the existence of the proposed filter are established such that the filtering error system is stochastically stable and preserves a guaranteed H"~ performance. A numerical example is provided to illustrate the effectiveness of the proposed filtering technique in this paper.
Ming Liu - One of the best experts on this subject based on the ideXlab platform.
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Observer-based sliding mode control for Itô stochastic time-delay systems with Limited Capacity channel
Journal of the Franklin Institute, 2012Co-Authors: Ming Liu, Guanghui SunAbstract:Abstract This paper investigates the problem of sliding mode control for a class of Ito stochastic time-delay systems over network communication links. The signals between plant and controller are exchanged over Limited Capacity channel, and are subject to logarithmic quantization before being transmitted. The main difficulty in this networked control problem is that, a sliding mode surface cannot be designed based on quantized outputs q ( y ( t ) ) directly since q ( y ( t ) ) is a piecewise constant and is not continuous in the quantizer switching times. To overcome this obstacle, in this paper, a state observer is designed to generate the estimation of system states, based on which a sliding mode controller is designed to stabilize the resulting closed-loop system. It is furthermore illustrated that the designing sliding mode controller can guarantee the reachability of the addressed sliding surface. A numerical simulation is performed to illustrate the effectiveness of the design control technique.
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h filtering for sampled data stochastic systems with Limited Capacity channel
Signal Processing, 2011Co-Authors: Ming Liu, Jia YouAbstract:This paper investigates the H"~ filtering problem for sampled-data stochastic systems with Limited Capacity channel. The considered plant is described by a class of Ito stochastic systems subject to external disturbance. The output measurements are sampled and quantized, and then transmitted through a network medium. The aim of this paper is focused on the design of full order filters by using the quantized sampled outputs. In sampled-data systems, the value of the sampled signal increases abruptly at sampling times, and traditional filter design results based on time-independent Lyapunov-Krasovskii functionals (or Lyapunov-Razumikhin functions) may be conservative. The main contribution of this paper is to propose a new type of time-dependent Lyapunov function for Ito stochastic systems which does not increase in sampling times due to its special mathematical structure. Based on this approach, sufficient conditions for the existence of the proposed filter are established such that the filtering error system is stochastically stable and preserves a guaranteed H"~ performance. A numerical example is provided to illustrate the effectiveness of the proposed filtering technique in this paper.
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H∞ filtering for sampled-data stochastic systems with Limited Capacity channel
Signal Processing, 2011Co-Authors: Ming Liu, Jia YouAbstract:This paper investigates the H"~ filtering problem for sampled-data stochastic systems with Limited Capacity channel. The considered plant is described by a class of Ito stochastic systems subject to external disturbance. The output measurements are sampled and quantized, and then transmitted through a network medium. The aim of this paper is focused on the design of full order filters by using the quantized sampled outputs. In sampled-data systems, the value of the sampled signal increases abruptly at sampling times, and traditional filter design results based on time-independent Lyapunov-Krasovskii functionals (or Lyapunov-Razumikhin functions) may be conservative. The main contribution of this paper is to propose a new type of time-dependent Lyapunov function for Ito stochastic systems which does not increase in sampling times due to its special mathematical structure. Based on this approach, sufficient conditions for the existence of the proposed filter are established such that the filtering error system is stochastically stable and preserves a guaranteed H"~ performance. A numerical example is provided to illustrate the effectiveness of the proposed filtering technique in this paper.
Jeremy M Wolfe - One of the best experts on this subject based on the ideXlab platform.
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signal detection evidence for Limited Capacity in visual search
Attention Perception & Psychophysics, 2011Co-Authors: Evan M Palmer, David E Fencsik, Stephen J Flusberg, Todd S Horowitz, Jeremy M WolfeAbstract:The nature of Capacity limits (if any) in visual search has been a topic of controversy for decades. In 30 years of work, researchers have attempted to distinguish between two broad classes of visual search models. Attention-Limited models have proposed two stages of perceptual processing: an unLimited-Capacity preattentive stage, and a Limited-Capacity selective attention stage. Conversely, noise-Limited models have proposed a single, unLimited-Capacity perceptual processing stage, with decision processes influenced only by stochastic noise. Here, we use signal detection methods to test a strong prediction of attention-Limited models. In standard attention-Limited models, performance of some searches (feature searches) should only be Limited by a preattentive stage. Other search tasks (e.g., spatial configuration search for a “2” among “5”s) should be additionally Limited by an attentional bottleneck. We equated average accuracies for a feature and a spatial configuration search over set sizes of 1–8 for briefly presented stimuli. The strong prediction of attention-Limited models is that, given overall equivalence in performance, accuracy should be better on the spatial configuration search than on the feature search for set size 1, and worse for set size 8. We confirm this crossover interaction and show that it is problematic for at least one class of one-stage decision models.
Andrey V. Savkin - One of the best experts on this subject based on the ideXlab platform.
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Decentralized Stabilization of Linear Systems via Limited Capacity Communication Networks
2005Co-Authors: Alexey S. Matveev, Andrey V. SavkinAbstract:The paper addresses feedback stabilization of discrete-time linear systems with multiple sensors, controllers, and actuators. The information is transmitted between them via a Limited Capacity deterministic communication network with arbitrary topology, which may be dynamically changed by nodes authorized to switch channels. The transferred messages may be delayed, corrupted or even lost; they may interfere and collide with each other. It is shown that the criterion for stabilizability is given by the network rate region, which answers to the question: how much information can be reliably transmitted from one set of points to another set of points. The system is stabiliazible if and only if a certain vector characterizing its rate of instability in the open-loop lies in the interior of the rate domain. In general, the rate domain of the primal network is not relevant here and a certain extension of the network should be employed. Furthermore, the relevant rate domain corresponds to a special subclass of decoders. In some cases, all decoders can be considered and this domain equals the standard one.
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robust stabilization of linear uncertain discrete time systems via a Limited Capacity communication channel
Systems & Control Letters, 2004Co-Authors: Vu Ngoc Phat, Andrey V. Savkin, Jianming Jiang, Ian R PetersenAbstract:Abstract The paper considers the problem of robust stabilization of linear uncertain discrete-time systems via Limited Capacity communication channels. We consider the case when the control input is to be transmitted via communication channel with a bit-rate constraint. A constructive method to design a robustly stabilizing controller is proposed.
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set valued state estimation via a Limited Capacity communication channel
Conference on Decision and Control, 2002Co-Authors: Andrey V. Savkin, Ian R PetersenAbstract:This paper considers a state estimation problem for a linear continuous-time system via a Limited Capacity communication channel. The observation must be coded and transmitted via a Limited Capacity digital communication channel. A recursive coder-decoder state estimation scheme is proposed and investigated.
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THE PROBLEM OF H∞ STATE ESTIMATION VIA Limited Capacity COMMUNICATION CHANNELS
IFAC Proceedings Volumes, 2002Co-Authors: Andrey V. SavkinAbstract:Abstract The paper presents a new approach to the problem of state estimation via Limited Capacity communication channels. We consider the case when the state estimates are required at a distant location, and are to be transmitted via a Limited Capacity communication channel. A constructive method to design a linear state estimator with a Limited Capacity communication channel is proposed.
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multi rate stabilization of multivariable discrete time linear systems via a Limited Capacity communication channel
Conference on Decision and Control, 2001Co-Authors: Ian R Petersen, Andrey V. SavkinAbstract:Presents an algorithm for the stabilization of a multi-input/multi-output discrete time linear system via a Limited Capacity channel. The approach taken is a deterministic multi-rate state space approach which leads to a nonlinear dynamic feedback controller.
Ian R Petersen - One of the best experts on this subject based on the ideXlab platform.
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robust stabilization of linear uncertain discrete time systems via a Limited Capacity communication channel
Systems & Control Letters, 2004Co-Authors: Vu Ngoc Phat, Andrey V. Savkin, Jianming Jiang, Ian R PetersenAbstract:Abstract The paper considers the problem of robust stabilization of linear uncertain discrete-time systems via Limited Capacity communication channels. We consider the case when the control input is to be transmitted via communication channel with a bit-rate constraint. A constructive method to design a robustly stabilizing controller is proposed.
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set valued state estimation via a Limited Capacity communication channel
Conference on Decision and Control, 2002Co-Authors: Andrey V. Savkin, Ian R PetersenAbstract:This paper considers a state estimation problem for a linear continuous-time system via a Limited Capacity communication channel. The observation must be coded and transmitted via a Limited Capacity digital communication channel. A recursive coder-decoder state estimation scheme is proposed and investigated.
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multi rate stabilization of multivariable discrete time linear systems via a Limited Capacity communication channel
Conference on Decision and Control, 2001Co-Authors: Ian R Petersen, Andrey V. SavkinAbstract:Presents an algorithm for the stabilization of a multi-input/multi-output discrete time linear system via a Limited Capacity channel. The approach taken is a deterministic multi-rate state space approach which leads to a nonlinear dynamic feedback controller.
