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Title: Recursive approximation of complex behaviours with IoT-data imperfections
Authors: Bekiroglu, Korkut
Srinivasan, Seshadhri
Png, Ethan
Su, Rong
Lagoa, Constantino
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Bekiroglu, K., Srinivasan, S., Png, E., Su, R., & Lagoa, C. (2020). Recursive approximation of complex behaviours with IoT-data imperfections. IEEE/CAA Journal of Automatica Sinica, 7(3), 656-667. doi:10.1109/jas.2020.1003126
Project: NRF2015ENC-GBICRD001-057 
Journal: IEEE/CAA Journal of Automatica Sinica 
Abstract: This paper presents an approach to recursively estimate the simplest linear model that approximates the time-varying local behaviors from imperfect (noisy and incomplete) measurements in the internet of things (IoT) based distributed decision-making problems. We first show that the problem of finding the lowest order model for a multi-input single-output system is a cardinality (ℓ 0 ) optimization problem, known to be NP-hard. To solve the problem a simpler approach is proposed which uses the recently developed atomic norm concept and the modified Frank-Wolfe (mFW) algorithm is introduced. Further, the paper computes the minimum data-rate required for computing the models with imperfect measurements. The proposed approach is illustrated on a building heating, ventilation, and air-conditioning (HVAC) control system that aims at optimizing energy consumption in commercial buildings using IoT devices in a distributed manner. The HVAC control application requires recursive thermal dynamical model updates due to frequently changing conditions and non-linear dynamics. We show that the method proposed in this paper can approximate such complex dynamics on single-board computers interfaced to sensors using unreliable communication channels. Real-time experiments on HVAC systems and simulation studies are used to illustrate the proposed method.
ISSN: 2329-9266
DOI: 10.1109/JAS.2020.1003126
Rights: © 2020 The Chinese Association of Automation. All rights reserved. This paper was published in IEEE/CAA Journal of Automatica Sinica and is made available with permission of the Chinese Association of Automation.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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