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Related Experiment Videos

Well-conditioned model predictive control.

Rickey Dubay1, Guy Kember, Bambang Pramujati

  • 1Department of Mechanical Engineering, University of New Brunswick, Fredericton, NB, Canada, E3B 5A3. dubayr@unb.ca

ISA Transactions
|March 6, 2004
PubMed
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A new dynamic matrix control (DMC) algorithm uses a "shifting factor" to improve control performance. This method enhances closed-loop dynamic responses for complex and fast processes compared to traditional DMC.

Area of Science:

  • Process Control
  • Control Engineering
  • Automation Systems

Background:

  • Model-based predictive control (MPC) offers advanced control but faces challenges with parameter selection and computational load for fast systems.
  • Existing MPC methods, including Dynamic Matrix Control (DMC), often rely on move suppression factors that can be ambiguous and computationally intensive.
  • Tight control of complex and fast-reacting processes remains a challenge with current control strategies.

Purpose of the Study:

  • To propose a novel Dynamic Matrix Control (DMC) algorithm that overcomes limitations of traditional methods.
  • To introduce a "shifting factor" (m) derived from open-loop data as an alternative to the move suppression coefficient.
  • To demonstrate improved control performance and closed-loop dynamic responses for complex and fast processes.

Related Experiment Videos

Main Methods:

  • Developed a new DMC algorithm allowing the process prediction time step to exceed the control time step.
  • Introduced a "shifting factor" (m) calculated from open-loop data to replace the move suppression coefficient in the controller matrix.
  • Validated the algorithm through practical demonstrations on a fast-reacting process and simulations on multivariable nonlinear models.

Main Results:

  • The new DMC algorithm with the shifting factor demonstrated superior control compared to DMC using move suppression on a fast-reacting process.
  • Improved closed-loop responses were observed in simulations for a multivariable nonlinear process with variable dead-time.
  • The shifting factor proved effective and generic, applicable across various control horizons and process models.

Conclusions:

  • The proposed shifting factor offers a more robust and computationally efficient alternative to move suppression in DMC.
  • This novel DMC approach enhances the control of complex, fast, and multivariable systems.
  • The generic nature of the shifting factor allows for broad applicability in advanced process control.