Comparing Fuzzy logic with classical controller designs
IEEE Transactions on Systems, Man and Cybernetics
PID type fuzzy controller and parameters adaptive method
Fuzzy Sets and Systems
Auto-tuning of fuzzy logic controllers for self-regulating processes
Fuzzy Sets and Systems
Multiple fuzzy model-based temperature predictive control for HVAC systems
Information Sciences: an International Journal
Fuzzy-genetic algorithm for automatic fault detection in HVAC systems
Applied Soft Computing
Design and simulation of self-tuning PID-type fuzzy adaptive control for an expert HVAC system
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
A New Pattern Recognition Adaptive Controller with Application to HVAC Systems
Automatica (Journal of IFAC)
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
Fuzzy sliding-mode control for ball and beam system with fuzzy ant colony optimization
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In this paper, a heating, ventilating and air-conditioning (HVAC) system was designed and two different damper gap rates (actuators position) of the HVAC system were controlled by a conventional PID (proportional-integral-derivative) controller. One of the dampers was controlled by using the required temperature for the interested indoor volume while the other damper was controlled by using the required humidity for the same indoor volume. The realized system has a zone with variable flow-rate by considering the ambient temperature and humidity. The required air flow was supplied by controlled of the dampers placed on the entrance ducts of indoor. Programmable Logic Controller (PLC) used PID control algorithm was utilized to control the system. This system has been controlled by a PLC based closed-loop controller. In this work, the realized system has been controlled by PLC used PID control algorithm. The optimal values of PID parameters were obtained by using Fuzzy sets. Fuzzy adaptive control has been performed to maximize the performance of the system. Efficiency of fuzzy adaptive control (FAC) developed method was successfully obtained.