Decoupling Fuzzy-Neural Temperature and Humidity Control in HVAC Systems
Иван Ганчев, Albena Taneva, Krum Kutryanski, Michail G. Petrov · IFAC-PapersOnLine · 2019
This paper presents a neuro-fuzzy structure of a decoupling fuzzy neural PID controller with self-tuning parameters. This structure is appropriate for heating, ventilation and air conditioning HVAC nonlinear plants. The main advantage here is that the equation of classical PID control with decoupling coefficients are used as a Sugeno function into the consequent part of the fuzzy rules. Hence, the designed decoupling fuzzy PID controller could be viewed as a natural similarity to the conventional PID controller with decoupling elements. A benchmark HVAC system with temperature and humidity control is considered to illustrate the benefits of the design paradigm. The performance of this set up was studied for reference tracking and disturbance rejection cases. Simulation results confirm the effectiveness of the proposed control system.