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Optimal linear LQG control over lossy networks without packet acknowledgment

TLDR
This paper is concerned with control applications over lossy data networks, and the discrete‐time linear quadratic Gaussian (LQG) optimal control problem is considered.
Abstract
This paper is concerned with control applications over lossy data networks. Sensor data is transmitted to an estimation-control unit over a network, and control commands are issued to subsystems over the same network. Sensor and control packets may be randomly lost according to a Bernoulli process. In this context, the discrete-time linear quadratic Gaussian (LQG) optimal control problem is considered. It is known that in the scenario described above, and for protocols for which there is no acknowledgment of successful delivery of control packets (e.g. UDP-like protocols), the LQG optimal controller is in general nonlinear. However, the simplicity of a linear sub-optimal solution is attractive for a variety of applications. Accordingly, this paper characterizes the optimal linear static controller and compares its performance to the case when there is acknowledgment of delivery of packets (e.g. TCP-like protocols). Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

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Foundations of Control and Estimation Over Lossy Networks

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Dynamic Watermarking: Active Defense of Networked Cyber–Physical Systems

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Survey of recent progress in networked control systems

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Networked Predictive Control of Uncertain Constrained Nonlinear Systems: Recursive Feasibility and Input-to-State Stability Analysis

TL;DR: The issue of guaranteeing the recursive feasibility of the optimization problem associated to the receding horizon control law has been addressed, and the networked closed-loop system has been proven to be Input-to-State Stable with respect to bounded perturbations.
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Stability analysis of networked control in smart grids

TL;DR: The closed-loop stability analysis framework has considered the limiting probability of data dropout in computing the stability margin and its contribution is in quantifying allowable data-dropout limit for a specified closed loop performance.
References
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Journal ArticleDOI

Kalman filtering with intermittent observations

TL;DR: This work addresses the problem of performing Kalman filtering with intermittent observations by showing the existence of a critical value for the arrival rate of the observations, beyond which a transition to an unbounded state error covariance occurs.
Journal ArticleDOI

Foundations of Control and Estimation Over Lossy Networks

TL;DR: In this paper, the authors consider control and estimation problems where the sensor signals and the actuator signals are transmitted to various subsystems over a network and characterize the impact of the network reliability on the performance of the feedback loop.
Journal ArticleDOI

Remote stabilization over fading channels

TL;DR: It is established that the set of plants which can be stabilized by linear controllers over fading channels is fundamentally limited by the channel generated uncertainty, and the notion of mean square capacity, defined for a single channel in the loop, captures this limitation precisely.
Journal ArticleDOI

Stability of Kalman filtering with Markovian packet losses

TL;DR: The notion of peak covariance is introduced, as an estimate of filtering deterioration caused by packet losses, which describes the upper envelope of the sequence of error covariance matrices {P"t,t>=1} for the case of an unstable scalar model.
Journal ArticleDOI

The matrix minimum principle

TL;DR: The purpose of this paper is to provide an alternate statement of the Pontryagin maximum principle as applied to systems which are most conveniently and naturally described by matrix, rather than vector, differential or difference equations.
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