Distributed Model Predictive Control based on Goal Coordination for Multi zone Building Temperature Control
For building HVAC control, this work provides a more efficient distributed control method with proven stability, addressing computational and energy challenges.
A distributed Model Predictive Control strategy for multi-zone building temperature control achieves 48% less computation time, 25.42% less energy consumption, and reduced tracking error compared to centralized MPC, with stability proofs and disturbance prediction.
In this paper, a distributed Model Predictive Control strategy is developed for a multi zone building plant with disturbances. The control objective is to maintain each zones temperature at a specified level with the minimum cost of the underlying HVAC system. The distributed predictive framework is introduced with stability proofs and disturbances prediction, which have not been considered in previous related works. The proposed distributed MPC performed with 48 percent less computation time, 25.42 percent less energy consumption, and less tracking error compared with the centralized MPC. The controlled system is implemented in a smart building test bed.