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Performance Characterization Using AoI in a Single-loop Networked Control System
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-5127-8497
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-5255-0352
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-9940-5929
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0001-6682-6559
2019 (English)In: IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM Workshops 2019, IEEE , 2019, p. 197-203Conference paper, Published paper (Refereed)
Abstract [en]

The joint design of control and communication scheduling in a Networked Control System (NCS) is known to be a hard problem. Several research works have successfully designed optimal sampling and/or control strategies under simplified communication models, where transmission delays/times are negligible or fixed. However, considering sophisticated communication models, with random transmission times, result in highly coupled and difficult-to-solve optimal design problems due to the parameter inter-dependencies between estimation/control and communication layers. To tackle this problem, in this work, we investigate the applicability of Age-of-Information (AoI) for solving control/estimation problems in an NCS under i.i.d. transmission times. Our motivation for this investigation stems from the following facts: 1) recent results indicate that AoI can be tackled under relatively sophisticated communication models, and 2) a lower AoI in an NCS may result in a lower estimation/control cost. We study a joint optimization of sampling and scheduling for a single-loop stochastic LTI networked system with the objective of minimizing the time-average squared norm of the estimation error. We first show that, under mild assumptions on information structure the optimal control policy can be designed independently from the sampling and scheduling policies. We then derive a key result that minimizing the estimation error is equivalent to minimizing a non-negative and non-decreasing function of AoI. The parameters of this function include the LTI matrix and the covariance of exogenous noise in the LTI system. Noting that the formulated problem is a stochastic combinatorial optimization problem and is hard to solve, we resort to heuristic algorithms by extending existing algorithms in the AoI literature. We also identify a class of LTI system dynamics for which minimizing the estimation error is equivalent to minimizing the expected AoI.

Place, publisher, year, edition, pages
IEEE , 2019. p. 197-203
Series
IEEE Conference on Computer Communications Workshops, ISSN 2159-4228
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-273065DOI: 10.1109/infcomw.2019.8845114ISI: 000526051100034Scopus ID: 2-s2.0-85069521542ISBN: 978-1-7281-1878-9 (print)OAI: oai:DiVA.org:kth-273065DiVA, id: diva2:1429566
Conference
IEEE Conference on Computer Communications (IEEE INFOCOM), APR 29-MAY 02, 2019, Paris, FRANCE
Note

QC 20200511

Available from: 2020-05-11 Created: 2020-05-11 Last updated: 2020-05-11Bibliographically approved

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Champati, Jaya PrakashMamduhi, Mohammad H.Johansson, Karl H.Gross, James

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