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A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Francisco Rego, Ye Pu, Andrea Alessandretti, A. Pedro Aguiar, A. Pascoal, Colin N. Jones

2020IEEE Transactions on Automatic Control33 citationsDOIOpen Access PDF

Abstract

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transmission. In the set-up adopted, sensors and actuators communicate through a network with a strongly connected topology. Unlike the case of centralized linear systems, for which the separation principle holds, the above practical assumption prevents the separate design of observers, and controller because each of the nodes does not necessarily have access to the control inputs generated at all the other nodes. We derive a linear distributed Luenberger observer, and a set of sufficient conditions that guarantee ultimate boundedness of the estimation error, and system state vectors, with bounds that depend on the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> norm of the noise signals, and the number of bits used in the transmissions. A numerical example illustrates the performance and effectiveness of the proposed algorithm in controlling a network of open-loop unstable systems.

Topics & Concepts

Observer (physics)Control theory (sociology)State observerLinear systemComputer scienceState (computer science)Network topologySeparation principleController (irrigation)Noise (video)MathematicsTopology (electrical circuits)AlgorithmControl (management)Artificial intelligenceComputer networkImage (mathematics)AgronomyNonlinear systemQuantum mechanicsCombinatoricsMathematical analysisPhysicsBiologyStability and Control of Uncertain SystemsTarget Tracking and Data Fusion in Sensor NetworksDistributed Sensor Networks and Detection Algorithms
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