Analysis of Control Methods for the Production Process of Composite Granular Fertilizers and the Necessity of Transitioning to Adaptive Control

Abstract

This article analyzes the existing methods of process control used in the production of composite granulated fertilizers (NPK and other multi-component mineral fertilizers) and substantiates the necessity of transitioning to adaptive control systems. The granulation process exhibits highly nonlinear and multifactorial behavior due to the instability of raw material composition, moisture content, and particle size distribution, as well as the interdependence of heat and mass transfer phenomena. The purpose of the study is to analyze the applicability of traditional control methods — PID, cascade and ratio control, and fuzzy-logic-based systems — to this process, to identify the limits of their effectiveness, and to substantiate the technical and economic rationale for transitioning to neural-network-based adaptive control systems. The study employed methods of scientific and technical literature analysis, comparative evaluation of existing control approaches, and generalization of industrial process data. The results show that under conditions of high variability in raw material composition and technological regime, classical control methods fail to ensure the stability of granule quality indicators, whereas the implementation of adaptive control systems can significantly improve product quality and reduce energy and resource consumption. The conclusion provides practical recommendations for a phased transition of the granulation process to adaptive control.