Design of Lyapunov Rule Based Model Reference Adaptive Control with Decoupler for Petroleum Distillation Column Control

The petroleum industry heavily relies on distillation as a key separation technique for product purification. Distillation columns, which include components such as trays, reboilers, condensers, and reflux drums, are essential for achieving efficient separations. However, controlling these columns is challenging due to their highly nonlinear nature, interactions between variables, and operational disturbances. Traditional Proportional-Integral-Derivative (PID) controllers, while widely used, struggle with multiple inputs and outputs, lack adaptability, and fail to handle dynamic changes effectively. This study introduces a Model Reference Adaptive Controller (MRAC) utilizing the Lyapunov adaptation rule to overcome existing challenges. The MRAC is implemented on a decoupled model of a petroleum distillation column, and its effectiveness is evaluated against a traditional PID controller. Simulation outcomes reveal that the MRAC outperforms the PID controller, exhibiting quicker response rates, minimized overshoot, and enhanced disturbance rejection capabilities. These findings suggest that the MRAC is a more efficient and robust control strategy for petroleum distillation column operations. For Liquefied petroleum gas (LPG) concentration, the MRAC improves rise time, settling time, and overshoot by 22.63%, 39.39%, and 34.23%, respectively, compared to the PID controller. Similarly, for gasoline concentration, improvements of 22.79%, 41.18%, and 40.26% are observed. Overall, MRAC outperforms PID controllers in stability and performance. When tested with a disturbance signal after settling time, MRAC demonstrates superior robustness and disturbance rejection capabilities.