Multivariable Model Predictive Control of Cleanroom Pressure Cascades

Cleanrooms are a fundamental setup of every semiconductor and life science factory, representing strictly controlled ambient conditions designed to minimize the air contamination that could affect a product within the production process. A cleanroom pressure cascade is a technological process associated with the ventilation and air treatment in these plants, with the goal of keeping the rooms within strict parameters. From a control systems perspective, it represents an MIMO ensemble of coupled control loops related to the technological process of air dynamics. In this research, we solve the multivariable control problem and present a novel, systematic approach with a conceptual solution for the following: (1) technological process and modeling challenges; (2) system identification and black-box MIMO process modeling; (3) full-blown controller design with model predictive control in its central place. This research was conducted on a real system at the “Fabrika COVID Vakcina” factory in Belgrade, Serbia.