Model predictive control of a HVAC system based on the LoLiMoT algorithm

In this paper a multi-variable control for the simultaneous control of the air temperature and the air humidity of an industrial heating ventilating and air conditioning (HVAC) system is presented. For the multi-input-multi-output (MIMO) control the model predictive control (MPC) method is applied. To model the system local linear neuro fuzzy models (LLNFM) are used and computed by the so-called Local Linear Model Tree (LOLIMOT) algorithm. The main focus of this work is the communication between the MPC and the LLNFMs and the application on a real world test plant. The proposed method is compared to a linear MPC scheme and a conventional PI control strategy.