Corpus ID: 11813266

Autoregressive Linear Thermal Model of a Residential Forced-Air Heating System with Backpropagation Parameter Estimation Algorithm

@inproceedings{Burger2017AutoregressiveLT,
  title={Autoregressive Linear Thermal Model of a Residential Forced-Air Heating System with Backpropagation Parameter Estimation Algorithm},
  author={Eric M. Burger and S. Moura and D. Culler},
  year={2017}
}
Model predictive control (MPC) strategies show great potential for improving the performance and energy efficiency of building heating, ventilation, and air-conditioning (HVAC) systems. A challenge in the deployment of such predictive thermostatic control systems is the need to learn accurate models for the thermal characteristics of individual buildings. This necessitates the development of online and data-driven methods for system identification. In this paper, we propose an autoregressive… Expand

References

SHOWING 1-10 OF 14 REFERENCES
Identifying models of HVAC systems using semiparametric regression
Online building thermal parameter estimation via Unscented Kalman Filtering
Issues in identification of control-oriented thermal models of zones in multi-zone buildings
Parameter identifiability for multi-zone building models
  • C. Agbi, Z. Song, B. Krogh
  • Engineering, Computer Science
  • 2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
  • 2012
State Estimation and Control of Electric Loads to Manage Real-Time Energy Imbalance
Receding-horizon supervisory control of green buildings
...
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