Comparing Neural Network and Linear Models in Economic MPC: Insights from BOPTEST for Building Temperature Control
Author:
Affiliation:
1. Purecontrol,Rennes,France,35000
2. UMR CNRS 6004, BP 92208,LS2N – Laboratory of digital sciences of Nantes,Nantes,44322
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10590709/10590710/10590813.pdf?arnumber=10590813
Reference31 articles.
1. Data-driven methods for building control — A review and promising future directions
2. Artificial neural network (ANN) based model predictive control (MPC) and optimization of HVAC systems: A state of the art review and case study of a residential HVAC system
3. Operating data of a specific Aquatic Center as a Benchmark for dynamic model learning: search for a valid prediction model over an 8-hour horizon
4. A comparative study of model approximation methods applied to economic MPC
5. Building optimization testing framework (BOPTEST) for simulation-based benchmarking of control strategies in buildings
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