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A Generalised Dynamic Matrix Control for unstable processes based on filtered predictions.

Tito L M Santos1, Julio E Normey-Rico2

  • 1Departamento de Engenharia Elétrica e de Computação (DEEC), Universidade Federal da Bahia (UFBA), Rua Aristides Novis, 02, Federação, CEP 40210-630, Salvador - BA, Brazil.

ISA Transactions
|December 1, 2022
PubMed
Summary
This summary is machine-generated.

A new Generalised Dynamic Matrix Control (GDMC) algorithm offers stable predictions for unstable processes. This data-driven approach improves control by ensuring internal stability, unlike traditional Dynamic Matrix Control (DMC).

Keywords:
Constrained systemsData-driven controlDynamic Matrix ControlUnstable systems

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Area of Science:

  • Process Control
  • Control Systems Engineering
  • Chemical Engineering

Background:

  • Open-loop unstable processes pose significant control challenges.
  • Traditional Dynamic Matrix Control (DMC) may not guarantee internal stability for such systems.
  • Advanced control strategies are needed for reliable process management.

Purpose of the Study:

  • To introduce a Generalised Dynamic Matrix Control (GDMC) algorithm.
  • To enable stable predictions for open-loop unstable processes.
  • To propose a novel data-driven filter design for internal stability.

Main Methods:

  • Development of the Generalised Dynamic Matrix Control (GDMC) algorithm.
  • Derivation of conditions for achieving internal stability in predictions.
  • Proposal of a new data-driven filter design procedure.
  • Simulation studies on two case examples.

Main Results:

  • The GDMC algorithm provides internally stable predictions for unstable processes.
  • The proposed filter design procedure is effective.
  • Simulation results demonstrate the practical utility of GDMC.

Conclusions:

  • GDMC is a viable and effective control strategy for open-loop unstable processes.
  • The generalized filtered approach ensures internal stability, a key advantage over DMC.
  • The data-driven filter design simplifies implementation and enhances performance.