Dynamic Modeling and Model Predictive Control of an Oxygen Distribution Pipeline System

Abstract Oxygen distribution pipelines are necessary infrastructure for delivering a consistent supply to a wide range of industries. However, the pipeline system also presents inherent risks associated with pure oxygen transport and the challenge of maintaining designed flow rate and pressure conditions, which must be controlled effectively. In this paper, an oxygen distribution pipeline system has been modeled and simulated with traditional proportional-integral-derivative (PID) controllers. To further improve its dynamic overall performance under a series of abrupt disturbances affecting control valves and pressures at key locations throughout the pipeline system, a model predictive control (MPC) strategy was also developed and virtually demonstrated. The simulation results demonstrate that MPC provides more effective and robust pressure regulation under abrupt disturbances, highlighting its capability to outperform traditional PID control and improve operator confidence in real-world oxygen pipeline applications.