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Related Experiment Videos

Auto-tuning of TITO decoupling controllers from step tests

Wang1, Huang, Guo

  • 1Department of Electrical Engineering, National University of Singapore, Singapore. elewqg@nus.edu.sg

ISA Transactions
|December 6, 2000
PubMed
Summary
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This study introduces robust auto-tuning for PI/PID controllers in two-input, two-output processes. The method effectively identifies process models for improved control system performance.

Area of Science:

  • Control Engineering
  • Process Automation
  • System Identification

Background:

  • Decentralized controllers offer advantages in complex industrial processes.
  • Tuning multivariable systems like two-input, two-output (TITO) processes remains challenging.
  • Existing methods may lack robustness or require extensive process knowledge.

Purpose of the Study:

  • To develop a robust auto-tuning methodology for TITO processes using decentralized PI/PID controllers.
  • To present a novel, robust identification method applicable to both single-input, single-output (SISO) and TITO systems.
  • To integrate model-based decoupler design with sequential PID controller tuning.

Main Methods:

  • A robust identification technique using step tests for SISO processes.

Related Experiment Videos

  • Sequential application of the identification method to TITO processes.
  • Design of a simple lead-lag decoupler based on a 1st-order plus dead-time (FOPDT) model.
  • Sequential tuning of decentralized PI/PID controllers using a 2nd-order process model.

    • Main Results:

    • Successful identification of SISO and TITO process models from step tests.
    • Effective design of lead-lag decouplers for TITO systems.
    • Demonstrated performance of the auto-tuned decentralized PI/PID controllers via simulation.
    • Robustness of the identification method shown in simulation examples.

    Conclusions:

    • The proposed auto-tuning method provides an effective approach for controlling TITO processes.
    • The robust identification technique is a key enabler for model-based decoupler and controller design.
    • This methodology simplifies the tuning of complex multivariable control systems.