INTELLIGENT SYSTEM FOR MONITORING AND MANAGEMENT OF THE VEGETABLE OIL REFINING PROCESS

This article examines the development and implementation of a system for optimal management of the multistage
technological process of refining vegetable oils based on predictive models and virtual quality analyzers. It has
been shown that traditional automatic control systems, based primarily on PID regulation, do not provide the required
level of quality and energy efficiency under conditions of uncertainty in parameters, nonlinearity, and multidimensionality
of the control object. An approach to building an improved management system using Model Predictive Control (MPC)
methods and virtual analyzers that provide an operational assessment of product quality indicators in real-time has been
proposed. The results of modeling and pilot production tests, confirming the increase in the stability of the technological
regime, the quality of the final product, and the reduction of specific energy costs, are presented