Utilization of aspen DMC3 in process control of crude distillation unit (CDU)

Abstract

Crude oil remains a vital non-renewable resource that supports numerous industries in the current era of industrial advancement. Consequently, petroleum refineries face increasing challenges, including stringent environmental regulations, fluctuating feedstock quality, rising demand, safety requirements, and the need for cost optimization. These challenges, coupled with the inherent complexity of the Crude Distillation Unit (CDU), demand advanced control strategies to ensure stable and efficient operation. This study investigates the application of Dynamic Matrix Control (DMC), a subset of Model Predictive Control (MPC), using Aspen DMC3 for CDU process control—a novel implementation not previously explored. The methodology involves three main stages: validation of a CDU simulation based on real data from the Basrah refinery, generation of dynamic response data through MATLAB integrated with Aspen Dynamics, and the development of a DMC controller using Aspen DMC3. The performance of the DMC controller is compared against conventional Proportional-Integral-Derivative (PID) controllers implemented in Aspen Dynamics using key indicators such as settling time, offset error, maximum deviation, and response smoothness. Results demonstrate that the DMC controller provides superior control performance, with faster settling times, zero offset, minimal deviations, and smoother responses. Additionally, Aspen DMC3′s AI-assisted capabilities enable streamlined controller configuration and real-time optimization through server connectivity, highlighting its potential for robust and efficient CDU operation.