A distributed virtual sensor scheme for smart buildings based on adaptive approximation

Vasso Reppa*, Panayiotis Papadopoulos, Marios M. Polycarpou, Christos G. Panayiotou

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

12 Citations (Scopus)

Abstract

This paper presents the design of a methodology for diagnosing sensor faults in heating, ventilation and air-conditioning (HVAC) systems, and compensating their effects on the distributed control architecture. The proposed methodology is developed in a distributed framework, considering a multi-zone HVAC system as a set of interconnected, nonlinear subsystems. For each of the interconnected subsystems, we design a local virtual sensor agent that can detect and isolate faults in its monitored sensors and provide sensor fault estimations for correcting the faulty measurements. Adaptive estimation schemes are implemented in each local virtual sensor agent, using adaptive approximation models for learning the unknown fault function. Simulation results are used for illustrating the effectiveness of the proposed methodology applied to a two-zone HVAC system.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherIEEE
Pages99-106
ISBN (Electronic)9781479914845
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing, China
Duration: 6 Jul 201411 Jul 2014

Conference

Conference2014 International Joint Conference on Neural Networks, IJCNN 2014
Country/TerritoryChina
CityBeijing
Period6/07/1411/07/14

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