Authors:
Luca Ferrarini
;
Soroush Rastegarpour
and
Anacleto Petretti
Affiliation:
Politecnico di Milano, Italy
Keyword(s):
Temperature Control, Self-tuning Regulators, Building Energy Efficiency, Model-based Control.
Related
Ontology
Subjects/Areas/Topics:
Adaptive Signal Processing and Control
;
Engineering Applications
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
System Modeling
Abstract:
The paper describes an interesting combination of auto-tuning and adaptive scheduling approaches to design and update a feedback/feedforward control of the temperature in buildings. The focus here is on residential houses endowed with radiant floors, which are intrinsically complex to control due to large inertia and operational constraints, and on the disturbance rejection of the external temperature. Pure auto-tuning techniques may fail to converge if the initialization step is not done properly, due to the wide variety of possible buildings and compensation hard to adapt in closed loop. The proposed approach combines a classification of the typology of rooms based on physical parameters with auto-tuning, so that in a two-step closed-loop procedure, the room cluster can be quickly identified, and consequently the feedback controller and feedforward compensator be tuned. Numerical examples are provided to test the robustness of the proposed approach.