Room Temperature Control Design for One-to-many Variable Refrigerant Flow Systems

This paper applies two control strategies of a Mamdani fuzzy logic control (FLC) and a Laguerre-based model predictive control (MPC) on the room temperature control of a one-to-many variable refrigerant flow (VRF) system. The fuzzy controller utilizes different input conditions to independently adjust the electronic expansion valve (EEV) opening and compressor speed. The MPC incorporates a Laguerre-function-based system model to reduce computational complexity while optimizing control performance through a weighted cost function. Both controllers were implemented and validated through simulations and experiments. Results show that the proposed methods maintain steady-state indoor temperature errors within 0.5°C and keep the evaporator superheat above 0°C. While the fuzzy logic controller offers better steady-state accuracy, the Laguerre-based model predictive controller demonstrates faster convergence to target temperatures. These findings suggest that both strategies are effective for improving temperature regulation in VRF systems.