Optimal Partitioning for the Decentralized Thermal Control of Buildings
- Resource Type
- Periodical
- Authors
- Chandan, V.; Alleyne, A.
- Source
- IEEE Transactions on Control Systems Technology IEEE Trans. Contr. Syst. Technol. Control Systems Technology, IEEE Transactions on. 21(5):1756-1770 Sep, 2013
- Subject
- Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Buildings
Vectors
Architecture
Distributed control
Temperature measurement
Robustness
Computer architecture
clustering
decentralized control
model predictive control
optimal control
- Language
- ISSN
- 1063-6536
1558-0865
2374-0159
This paper studies the problem of thermal control of buildings from the perspective of partitioning them into clusters for decentralized control. A measure of deviation in performance between centralized and decentralized control in the model predictive control framework, referred to as the optimality loss factor, is derived. Another quantity called the fault propagation metric is introduced as an indicator of the robustness of any decentralized architecture to sensing or communication faults. A computationally tractable agglomerative clustering approach is then proposed to determine the decentralized control architectures, which provide a satisfactory trade-off between the underlying optimality and robustness objectives. The potential use of the proposed partitioning methodology is demonstrated using simulated examples.