A multiple model approach for predictive control of indoor thermal environment with high resolution

Abstract

Realtime and precise control strategies for indoor micro-climate are increasingly needed due to the requirements of thermal comfort and energy consumption saving in recent years. In this paper, a precise control scheme with high resolution is proposed for indoor thermal regulation. Finite volume method discretization/linearization are employed to construct the state-space model of the thermal process. Proper orthogonal decomposition method is further applied for model order reduction. On this basis, a multiple model approach is used to treat the thermodynamic coupling effect and a multi-model switching model predictive control (MPC) scheme is proposed for temperature tracking. Two cases including cooling and warming scenarios are designed, respectively, for performance validation. Results show that compared with the classic MPC method, the developed method can alleviate the model mismatch problem, and facilitate an optimal control of the spatial temperature in the considered ventilation room.