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Multi-objective predictive control based on the cutting tobacco outlet moisture priority.

Zhiping Fan1,2, Zhengyun Ren3, Angang Chen4

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This study introduces a new priority optimization strategy for cutting tobacco processes, enhancing control over moisture levels. The method demonstrates robust performance and improved tracking compared to traditional approaches in drying applications.

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Area of Science:

  • Chemical Engineering
  • Process Control
  • Optimization Theory

Background:

  • Cutting tobacco drying involves complex multi-objective optimization challenges.
  • Existing control strategies often lack robustness and precise tracking in dynamic environments.

Purpose of the Study:

  • To develop a novel priority multi-objective optimization strategy for cutting tobacco drying.
  • To enhance system output variable control, particularly moisture levels.
  • To provide advanced technical support for the chemical industry's drying processes.

Main Methods:

  • Implementation of a two-level priority-based optimization for system output variables.
  • Utilizing strict set-point control for critical variables and zone control for others.
  • Sequential optimization of variables in ascending priority order with constraint relaxation.

Main Results:

  • The proposed strategy ensures system control output variables move along an optimal target trajectory.
  • Demonstrated good robustness against disturbances in cutting tobacco drying simulations.
  • Exhibited superior tracking performance compared to traditional predictive control methods.

Conclusions:

  • The novel strategy offers effective technical support for drying processes in the chemical industry.
  • The approach provides a robust and high-performance solution for multi-objective optimization in cutting tobacco drying.
  • This method surpasses traditional predictive control in real-world applications.