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Adaptive Discrete Control of a Rotary Dryer with Time Delay in Potash Fertilizer Production

Akmalbek AbdusalomovDepartment of Computer Engineering, Gachon University Sujeong-Gu, Seongnam-si 13120, Gyeonggi-Do, Republic of KoreaSuban KhusanovAutomation and Control of Technological Processes, Karshi State Technical University, Karshi 180100, UzbekistanIslomnur IbragimovAutomation and Control of Technological Processes, Karshi State Technical University, Karshi 180100, UzbekistanJasur SevinovDepartment of Computer Engineering, University of Tashkent for Applied Sciences, Tashkent 100149, UzbekistanMukhriddin MukhiddinovDepartment of Artificial Intelligence, Tashkent University of Information Technologies Named After Muhammad Al-Khwarizmi, Tashkent 100200, UzbekistanYoung Im ChoDepartment of Computer Engineering, Gachon University Sujeong-Gu, Seongnam-si 13120, Gyeonggi-Do, Republic of Korea
Processesjournal2026en
ABI

Аннотация

This paper presents the design and industrial implementation of an adaptive discrete control system for a rotary dryer operating in potash fertilizer production. The drying process is characterized by high inertia, multivariable interactions, transport delay, and non-stationary behavior resulting from variations in raw material properties and external disturbances, which significantly reduce the effectiveness of conventional fixed-parameter controllers. A discrete-time mathematical model of the rotary drying process was developed using industrial experimental data collected from a full-scale production plant. The process was modeled as a coupled 2 × 2 multivariable system with pronounced time-delay effects in the main control channels. System identification was carried out using statistical and frequency-domain methods to capture the dominant dynamic characteristics required for controller synthesis. Based on the identified model, an adaptive discrete controller with online parameter adjustment was developed to regulate outlet moisture content and exhaust gas temperature. Simulation and industrial results confirmed stable operation under varying conditions, improved regulation accuracy, enhanced process stability, and an average production efficiency increase of approximately 1.8%, accompanied by reduced fuel consumption.

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