Intelligent Fuzzy-PID Temperature Control System for Ensuring Comfortable Microclimate in an Intelligent Building

In an era characterized by the growing significance of energy-efficient and human-centric environmental control systems, this research endeavors to investigate the efficacy of a Fuzzy Proportional-Integral-Derivative (PID) control approach for temperature regulation within Heating, Ventilation, and Air Conditioning (HVAC) systems. The study leverages the adaptability and robustness of fuzzy logic to dynamically tune the PID controller's parameters in response to changing environmental conditions. Through comprehensive simulations and comparative analyses, the research showcases the superior performance of the proposed fuzzy PID control system in terms of rapid response, overload avoidance, and minimal steady-state error, particularly when contrasted with conventional PID control and model predictive control (MPC) methodologies. Furthermore, the research extends its scope to assess the control system's resilience in the face of significant load variations, affirming its practical applicability in real-world HVAC scenarios. Beyond its immediate implications for HVAC systems, this research underscores the broader potential of fuzzy PID control in enhancing control precision and adaptability across various domains, including robotics, industrial automation, and process control. By advocating for future research endeavors in optimizing fuzzy membership functions, implementing real-time solutions, and exploring multi-objective optimization, among other avenues, this study seeks to contribute to the ongoing discourse surrounding advanced control strategies for achieving energy-efficient and human-centric environmental regulation.

@article{Abdrakhmanov2024,
  title     = {Intelligent Fuzzy-PID Temperature Control System for Ensuring Comfortable Microclimate in an Intelligent Building},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {3},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Rustam Abdrakhmanov and Kamalbek Berkimbayev and Angisin Seitmuratov and Almira Ibashova and Akbayan Aliyeva and Gulira Nurmukhanbetova},
  doi       = {10.14569/IJACSA.2024.0150331},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150331}
}