An Intelligent Fuzzy-PID Controller for Supporting Comfort Microclimate in Smart Homes

Abstract

Addressing the challenge of ensuring a comfortable indoor environment in both commercial and residential buildings through the use of heating, ventilation, and air conditioning (HVAC) systems is a critical issue. This challenge is intricately connected to the development of sophisticated multi-channel controllers to regulate temperature and humidity effectively. This academic discussion initially focuses on the development and examination of a complex, interactive, nonlinear mathematical model that encapsulates the ideal parameters for temperature and humidity to achieve the desired comfort levels. The paper then progresses to explore various methodologies in the design of temperature and humidity control systems. It delves into the traditional Proportional-Integral-Derivative (PID) controllers, a mainstay in the industry, and extends to more advanced iterations. These include the integration of PID controllers with distinct decoupled controllers and the innovative combination of PID controllers with self-adjusting parameters, which are informed by the principles of fuzzy logic. This combination is particularly significant for the processes of heating and humidification. Subsequently, the paper presents the results obtained from simulations conducted on a proposed fuzzy-PID controller using Matlab, a widely used computational tool. These simulations are crucial in evaluating the efficacy of the controller design. Additionally, the paper offers an analysis of experimental data collected over a six-month period. This data is instrumental in assessing the real-world performance of the proposed system, providing valuable insights into its practical applicability and effectiveness in managing indoor climate conditions. In summary, this comprehensive study not only lays the groundwork for an interactive model for climate control but also compares various controller designs, culminating in the proposal and evaluation of an advanced fuzzy-PID controller. This work stands as a significant contribution to the ongoing efforts to enhance indoor climate control in buildings.