Research Theme: Building Automation and Reliability Our research aims to promote the reliability of the control system of a building, which provides the functionality for building automation systems, and follows the mind map shown in Figure below. We want to promote the reliability of building automation system by enhancing the reliability of measurement, control and management. Measurement reliability will be enhanced by the sensor/data fusion technique; control reliability will be enhanced by robust control design which takes uncertainties, nonlinearities and constraints into account; and management reliability will be enhanced by the data mining technology. Current achievements include: Robust model-based predictive control (MPC) has been developed to improve the robustness of the temperature control of VAV and CAV air conditioning systems; A chiller-model-based data fusion approach has been developed to enhance the reliability of chiller sequencing control; A multiple-sensor-based data fusion approach has been developed to improve the reliability of building cooling load for chiller plants; A data fusion approach has been developed for heat pump systems for accurate performance evaluation Mind Map of Building Automation and Reliability Research Current Group Members: Dr. Gongsheng HUANG Miss Yundan LIAO (MEng, Guanzhou University; PhD student) Mr. Pei HUANG (Huazhong University of Science and Technology; PhD student) Mr. Pei ZHOU (MEng, Tongji University; PhD student) Mr. Junqi WANG (MSc, the University of Hong Kong; PhD student) Previous Members Mr. Linfeng Zhang (MEng, Hunan University) Dr. Zhengwei Li (PhD, Georgia Institute of Technology ) Mr. Qiuyuan ZHU (Huazhong University of Science and Technology) Dr. Peng Li (Associate Professor, Tongji University)

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