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. ; © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. V. Reppa, P. M. Papadopoulos, M. M. Polycarpou and C. G. Panayiotou, "A distributed virtual sensor scheme for smart buildings based on adaptive approximation," in Proceedings of International Joint Conference on Neural Networks, pp. 99-106, 2014. doi:10.1109/IJCNN.2014.6889976
A distributed virtual sensor scheme for smart buildings based on adaptive approximation
2014-09-04
Conference paper
Electronic Resource
English
DDC: | 629 |
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