Recursive Approximation of Complex Behaviours With IoT-Data Imperfections  

作　　者：Korkut Bekiroglu Seshadhri Srinivasan Ethan Png Rong Su Constantino Lagoa 

机构地区：[1]College of Engineering,SUNY Polytechnic Institute,Utica 13503,NY,USA [2]Berkeley Education Alliance for Research in Singapore(BEARS),Singapore 138602,Singapore [3]School of Electrical and Electronic Engineering,Nanyang Technological University,Singapore 639798,Singapore [4]IEEE [5]Electrical Engineering Department of Pennsylvania State University,Park,PA 16802 USA

出　　处：《IEEE/CAA Journal of Automatica Sinica》2020年第3期656-667,共12页自动化学报（英文版）

基　　金：supported by the Building and Construction Authority through the NRF GBIC Program(NRF2015ENC-GBICRD001-057)。

摘　　要：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(l0) 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.

关 键 词：ADAPTABILITY distributed decision systems imperfect measurements internet of things(IoT) low order model identification 

分 类 号：TU111.195[建筑科学—建筑理论] TN929.5[电子电信—通信与信息系统] TP391.44[电子电信—信息与通信工程]