An Integrated Multi-Scale Stochastic Framework for Dynamic Analysis and Control of Transport Phenomena in Building Systems

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

Abstract This project proposes a Dynamical Systems based integrated framework for analysis, detection, and control of transport processes in diverse Building systems applications. The premise of this proposal is that the complexity of transport models is a key technical barrier that prevents effective integrated building system solutions. CFD-based Monte-Carlo simulations for assessing performance is not efficient and complex models are ill-suited for detection, control or design. The objective of the proposal is to develop and demonstrate computationally a mathematical framework that enables a) dynamic analysis, b) study of fundamental limitations in performance, c) sensor architecture definition, and d) detection and control design for complex transport problems in building systems. The innovation of this proposal lies in the re-casting of the transport models as Markov chains on graphs. Markov chains are constructed using efficient set-oriented methods to propagate uncertainty in a multi-scale fashion. This idea incorporates a multi-scale complexity reduction approach to diverse problems in building systems and hence provides for an integrated modeling framework. The approach further has the potential (that will be rigorously explored) to exploit recent advances in both Dynamical Systems and Control Theory.