Finite-time behavior of switching networks

Cavalcanti, João M. B.; Balakrishnan, Hamsa

doi:10.1109/cdc.2017.8264639

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…In this work we assume that these transitions are independent of the past, i.e., the discrete parameter is an independent and identically distributed random variable. JLSs have been used in economics [1] where each mode corresponds to a business cycle and the state is economic growth; in statistics [2] to model multiple related time series, where each series is generated from a single mode; and large infrastructure systems such as air traffic networks [3].…”

Section: Introductionmentioning

confidence: 99%

Minimal Realization Problems for Jump Linear Systems

Sarkar

Roozbehani

Dahleh

2018

2018 IEEE Conference on Decision and Control (CDC)

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This paper addresses two fundamental problems in the context of jump linear systems (JLS). The first problem is concerned with characterizing the minimal state space dimension solely from input-output pairs and without any knowledge of the number of mode switches. The second problem is concerned with characterizing the number of discrete modes of the JLS. For the first problem, we develop a linear system theory based approach and construct an appropriate Hankellike matrix. The rank of this matrix gives us the state space dimension. For the second problem we show that minimal number of modes corresponds to the minimal rank of a positive semi-definite matrix obtained via a non-convex formulation.

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Section: Introductionmentioning

confidence: 99%

Minimal Realization Problems for Jump Linear Systems

Sarkar

Roozbehani

Dahleh

2018

2018 IEEE Conference on Decision and Control (CDC)

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Control and Optimization of Air Traffic Networks

Gopalakrishnan

Balakrishnan

2021

Annu. Rev. Control Robot. Auton. Syst.

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The air transportation system connects the world through the transport of goods and people. However, operational inefficiencies such as flight delays and cancellations are prevalent, resulting in economic and environmental impacts. In the first part of this article, we review recent advances in using network analysis techniques to model the interdependencies observed in the air transportation system and to understand the role of airports in connecting populations, serving air traffic demand, and spreading delays. In the second part, we present some of our recent work on using operational data to build dynamical system models of air traffic delay networks. We show that Markov jump linear system models capture many of the salient characteristics of these networked systems. We illustrate how these models can be validated and then used to analyze system properties such as stability and to design optimal control strategies that limit the propagation of disruptions in air traffic networks. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Finite-time behavior of switching networks

Cited by 2 publications

References 22 publications

Minimal Realization Problems for Jump Linear Systems

Minimal Realization Problems for Jump Linear Systems

Control and Optimization of Air Traffic Networks

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