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Tuning strategy for dynamic matrix control with reduced horizons.

Tomasz Klopot1, Piotr Skupin1, Mieczyslaw Metzger1

  • 1Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland.

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We propose a tuning strategy for Dynamic Matrix Control (DMC) that reduces computational load. This method lowers memory requirements for industrial controllers without compromising control quality, making advanced process control more accessible.

Keywords:
DMCPLCPredictive controlTuning rules

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Area of Science:

  • Process Control
  • Automation Engineering
  • Industrial Computing

Background:

  • Dynamic Matrix Control (DMC) offers superior control, particularly for systems with significant time delays.
  • Implementing DMC in industrial settings faces challenges due to limited computational resources in devices like Programmable Logic Controllers.
  • Existing DMC algorithms may require substantial memory, hindering their application in resource-constrained local control loops.

Purpose of the Study:

  • To develop a tuning strategy for the DMC algorithm that addresses computational limitations.
  • To reduce the memory footprint of DMC implementation in industrial controllers.
  • To maintain or improve control quality while decreasing resource demands.

Main Methods:

  • A novel tuning strategy for the DMC algorithm was developed.
  • The strategy involves reducing the lengths of the prediction and dynamic horizons.
  • The impact of horizon reduction on computational requirements and control performance was analyzed.

Main Results:

  • The proposed tuning strategy effectively reduces the memory requirements for DMC implementation.
  • Reduction in prediction and dynamic horizons leads to decreased computational load.
  • Control quality is maintained despite the reduction in horizon lengths, demonstrating the strategy's efficacy.

Conclusions:

  • The developed tuning strategy enables efficient implementation of DMC in industrial controllers with limited resources.
  • Reduced horizons in DMC offer a practical solution for deploying advanced process control in constrained environments.
  • This approach enhances the feasibility of using DMC for improved automation and control quality in industrial applications.