Title :
Building temperature control with adaptive feedforward
Author :
Wen, John T. ; Mishra, Shivakant ; Mukherjee, Sayan ; Tantisujjatham, Nicholas ; Minakais, Matt
Author_Institution :
Comput. & Syst. Eng. Dept., Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
A common approach to the modeling of temperature evolution in a multi-zone building is to use thermal resistance and capacitance to model zone and wall dynamics. The resulting thermal network may be represented as an undirected graph. The thermal capacitances are the nodes in the graph, connected by thermal resistances as links. The temperature measurements and temperature control elements (heating and cooling) in this lumped model are collocated. As a result, the input/output system is strictly passive and any passive output feedback controller may be used to improve the transient and steady state performance without affecting the closed loop stability. The storage functions associated with passive systems may be used to construct a Lyapunov function, to demonstrate closed loop stability and motivate the construction of an adaptive feedforward control to compensate for the variation of the ambient temperature and zone heat loads (due to changing occupancy). The approach lends itself naturally to an inner-outer loop control architecture where the inner loop is designed for stability, while the outer loop balances between temperature specification and power consumption. Energy efficiency consideration may be added by adjusting the target zone temperature based on user preference and energy usage. The initial analysis uses zone heating/cooling as input, but the approach may be extended to more general model where the zonal mass flow rate is the control variable. A four-room example with realistic ambient temperature variation is included to illustrate the performance of the proposed passivity based control strategy.
Keywords :
HVAC; Lyapunov methods; adaptive control; closed loop systems; feedback; feedforward; graph theory; stability; temperature control; thermal resistance; Lyapunov function; adaptive feedforward control; ambient temperature; building temperature control; closed loop stability; cooling; energy efficiency; energy usage; heating; inner-outer loop control architecture; multizone building; passive output feedback controller; passivity based control; power consumption; storage function; temperature evolution; temperature measurement; temperature specification; thermal capacitance; thermal network; thermal resistance; undirected graph; user preference; wall dynamics; zonal mass flow rate; zone heat load; Atmospheric modeling; Buildings; Feedforward neural networks; Heating; Thermal resistance; Thermal stability;
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
Print_ISBN :
978-1-4673-5714-2
DOI :
10.1109/CDC.2013.6760646