Wu, Hung-TingHung-TingWuChou, Hsin-HaoHsin-HaoChouWu, Yi-ChinYi-ChinWuCHUN-YEON LINWang, Chien-ChangChien-ChangWangNian, Shy-HerShy-HerNianTsai, Meng-YenMeng-YenTsaiHung, Tsai-WangTsai-WangHung2025-11-252025-11-252025979833153342721596247https://www.scopus.com/record/display.uri?eid=2-s2.0-105018742642&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/734115This 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.false[SDGs]SDG7conference paper10.1109/AIM64088.2025.111758592-s2.0-105018742642