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|Title:||Studies on the robustness of DCC-AB method subject to communication failures||Authors:||Chen, Yanhong||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering||Issue Date:||2019||Abstract:||With the continuous development of urbanization, urban residents spend most of their time indoors, making the indoor air quality (IAQ) an even more significant issue. The ventilation rate is a critical factor that affects both the IAQ and energy consumption of the heating, ventilation, and air conditioning (HVAC) system. This dissertation mainly focuses on the study of the flow imbalance problem in ventilation systems and identifies the challenges faced by air balancing. An online distributed cooperative control-based air balancing (DCC-AB) method is studied and validated in the experimental platform, and the robustness of this method subject to communication failure is investigated. Firstly, the consensus theory in multi-agent systems is studied, and related literature review on the algebraic graph theory is conducted. Based on the properties of graph theory and graph matrices, the condition for consensus of a multi-agent system is specified, and the corresponding protocol is given. Then, a series of simulations are conducted in MATLAB to study the convergence of the method subject to communication failures. The simulation results demonstrate that the consensus is attainable using the DCC-AB method even in the presence of communication failures. The selection of the adjacency matrix on the performance of the DCC-AB method is investigated. Finally, the DCC-AB method is validated on the experimental platform and the robustness subject to communication failures is examined. The simulation and experimental results reveal that the DCC-AB method could achieve the air balance of the duct system as long as there is a spanning tree in the adjacency matrix. The DCC-AB method demonstrates good robustness in the presence of communication fault, making it a preferable choice in industrial applications.||URI:||http://hdl.handle.net/10356/78449||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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