Selecting building predictive control based on model uncertainty

ACC(2014)

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摘要
Model uncertainty limits the utilization of Model Predictive Controllers (MPC) to minimize building energy consumption. We propose a new Robust Model Predictive Control (RMPC) structure to make a building controller robust to model uncertainty. The results from RMPC are compared with those from a nominal MPC and a common building Rule Based Control (RBC). The results are then used to develop a methodology for selecting a controller type (i.e. RMPC, MPC, and RBC) as a function of building model uncertainty. RMPC is found to be the desirable controller for the cases with an intermediate level (30%-67%) of model uncertainty, while MPC is preferred for the cases with a low level (0-30%) of model uncertainty. A common RBC is found to outperform MPC or RMPC if the model uncertainty goes beyond a certain threshold (e.g. 67%).
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关键词
building energy consumption,robust control,predictive control for linear systems,hvac,rmpc structure,rbc,robust model predictive controller,energy consumption,building and facility automation,buildings (structures),common building rule based control,building model uncertainty function,predictive control,engineering,mathematical model,heating,temperature measurement,robustness,uncertainty,atmospheric modeling
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