Performance Evaluation of Smart Systems under Uncertainty

TitlePerformance Evaluation of Smart Systems under Uncertainty
Publication TypeConference Proceedings
Year of Conference2017
AuthorsNannapaneni, S., A. Dubey, and S. Mahadevan
Conference NameIEEE Smart World Congress
Date Published08/2017

This paper develops a model-based framework for the quantification and propagation of multiple uncertainty sources affecting the performance of a smart system. A smart system, in general, performs sensing, control and actuation for proper functioning of a physical subsystem (also referred to as a plant). With strong feedback coupling between several subsystems, the uncertainty in the quantities of interest (QoI) amplifies over time. The coupling in a generic smart system occurs at two levels: (1) coupling between individual subsystems (plant, cyber, actuation, sensors), and (2) coupling between nodes in a distributed computational subsystem. In this paper, a coupled smart system is decoupled and considered as a feed-forward system over time and modeled using a two-level Dynamic Bayesian Network (DBN), one at each level of coupling (between subsystems and between nodes). A DBN can aggregate uncertainty from multiple sources within a time step and across time steps. The DBN associated with a smart system can be learned using available system models, physics models and data. The proposed methodology is demonstrated for the design of a smart indoor heating system (identification of sensors and a wireless network) within cost constraints that enables room-by-room temperature control. We observe that sensor uncertainty has a higher impact on the performance of the heating system compared to the uncertainty in the wireless network.

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