Research on Temperature Control Method of Rice Noodles Extruder Based on APSO-MPC

Area of Science:

• Food Engineering
• Control Systems Engineering
• Thermodynamics

Background:

• Existing rice noodle extruders suffer from temperature control disturbances and hysteresis.
• Accurate temperature control is crucial for consistent rice noodle quality.

Purpose of the Study:

• To design an advanced temperature control method for rice noodle extruders.
• To address limitations of existing control systems, specifically disturbances and hysteresis.

Main Methods:

• Developed a temperature prediction model based on thermodynamic analysis of the extruder barrel.
• Employed Adaptive Particle Swarm Optimization (APSO) for model parameter identification.
• Implemented Model Predictive Control (MPC) with APSO for optimal temperature regulation.
• Integrated feed rate feedforward control to mitigate fluctuations.

Main Results:

• Achieved a maximum temperature overshoot of 7.75%.
• Maintained steady-state error within ±1 °C.
• Demonstrated superior adaptability and control accuracy compared to fuzzy PID control.

Conclusions:

• The proposed APSO-MPC method significantly enhances temperature control precision in rice noodle extruders.
• This advanced control strategy effectively minimizes disturbances and hysteresis, leading to improved product consistency.
• The method offers a robust solution for optimizing the extrusion process.