Development of an Intelligent System for Managing the Oil Rectification Process

The article presents an intelligent control system for the oil rectification process based on the hybrid application of a genetic algorithm (GA) and gradient optimization methods. The developed system ensures the automatic maintenance of optimal process parameters for the rectification column, such as temperature at different sections, phlegm ratio, pressure, and level in the cube, in order to minimize energy consumption while maintaining the required quality of the separation products. Experimental studies on a simulation model of a rectification column showed that the proposed GA+GD hybrid system reduces energy consumption by 12-18% compared to classical PID controllers, while providing higher accuracy in maintaining the composition of target fractions. The system automatically adapts to changes in the composition of raw materials and external conditions, which is confirmed by the results of transient mode simulations.