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Controller design for optimal operation of Multiple Effect Evaporator of paper mills

  • Drishti Yadav
  • , Nikhil Pachauri
  • , Om Prakash Verma*
  • , Deepak Sahu
  • , Jatinder Kumar Ratan
  • , Tarun Kumar Sharma
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The Kraft recovery process in the paper mills is highly complex and nonlinear. The evaporation of black liquor using Multiple Effect Evaporators (MEE) in the recovery unit of the Kraft process is an energy-consuming procedure. The challenge lies in designing a proficient control strategy to conserve energy and guarantee good product quality. In this article, the 2-DOF-PI controller is designed to enable efficient control of MEE and eliminate process uncertainties. The Heptads’ Effect Falling Film Evaporator in the backward feed flow configuration is used as a working platform. The steady-state and transient behavior of MEE is modeled and analyzed to assist in controller design. The steady-state process parameters, that guarantee optimum energy efficiency, are estimated using Moth–Flame Optimization (MFO). MFO is also employed to estimate the optimal 2-DOF-PI controller parameters to attain improved product quality and energy-efficient performance of MEE. The competence of MFO towards controller tuning is shown by a fair comparison with some well-known optimization techniques. The quantitative investigation of the statistical results demonstrates that MFO outperforms the other algorithms. To validate the proficiency of the designed control scheme, its performance is compared with basic PI/PID control strategy for set-point tracking, noise suppression, and process uncertainties. The simulation results indicate that the designed MFO-tuned 2-DOF-PI controller offers efficient control action and, therefore, proves to be an appropriate control algorithm to ensure sustainable production.

    Original languageEnglish
    Article number100137
    JournalResults in Control and Optimization
    Volume8
    DOIs
    Publication statusPublished - 09-2022

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Modelling and Simulation
    • Control and Optimization
    • Applied Mathematics
    • Artificial Intelligence

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