Design of Natural Ventilation Optimal Control System to Achieve Desirable Room Temperature and to Tolerate Uncertain Variants

• Author / Creator

  Hameed, Muhammad Ahmad

• Natural ventilation models are becoming increasingly popular with increasing environmental awareness and the adverse effect of mechanical ventilation systems on the environment. Though simple in their working principle, natural ventilation models are challenging to control in meeting the thermal comfort demands of the occupants in changing weather conditions. This requires robust environment control and precise climatic parameters prediction for satisfactory performance. This study aims to design and assess the performance of optimal controllers for natural ventilation. Three optimal controllers, Linear Quadratic Regulator (LQR), Linear Quadratic Integral (LQI), and Linear Quadratic Gaussian (LQG), have been developed and assessed for their performance for thermal comfort for a naturally ventilated modeled with its window as the control input. In addition to these three controllers, another more efficient optimal predictive controller known as Model Predictive Controller is also designed and applied to the natural ventilation system. The three controllers are also compared with a Model Predictive Controller (MPC). Considering natural ventilation as a natural process with slower changing dynamics and subjected to various external and internal system uncertainties, the MPC is shown to outperform the other optimal controllers in terms of robust temperature prediction and control, efficient disturbance rejection, and uncertainty handling. Another challenge addressed by the study is the development of a simplified mathematical model that can be utilized for building a robust real-time controller. With an efficient runtime of 0.08 sec per optimization, the MPC shows robust temperature control by providing thermal comfort to users. This is achieved with a Predicted Mean Vote (PMV) index of 0.0013, which shows the controller performs effectively to keep the thermal comfort of the occupants to an acceptable level.

• Subjects / Keywords

  • Optimal Control
  • Natural Ventilation Controls
  • Thermal Comfort
  • Control Design
  • LQR
  • LQG
  • MPC

• Graduation date

  Spring 2023

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-7j3d-0k46

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.