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Related Experiment Videos

Model predictive control with amplitude and rate actuator saturation.

Leonardo L Giovanini1

  • 1Electronic and Control Research Group, Universidad Tecnológica Nacional, Regional School at Villa Maria, Av. Universidad 450, 5900 Villa Maria, Argentina. lgiovani@fich1.unl.edu.ar

ISA Transactions
|April 24, 2003
PubMed
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This study reveals how anti-wind-up bumpless transfer controllers arise from model predictive control (MPC) with input constraints. This framework ensures actuator limits are respected and controller states are updated effectively.

Area of Science:

  • Control Engineering
  • Automation Systems

Background:

  • Model Predictive Control (MPC) is a widely used advanced control strategy.
  • Controller windup and bumpless transfer are critical issues in practical control applications.
  • Input constraints are essential for safe and efficient actuator operation.

Purpose of the Study:

  • To demonstrate the emergence of anti-wind-up bumpless transfer control from Model Predictive Control (MPC).
  • To establish a theoretical link between MPC with input constraints and bumpless transfer behavior.
  • To present a novel control framework incorporating physical constraint models.

Main Methods:

  • Application of optimality conditions to an equivalent optimal control problem.
  • Development of a controller architecture that integrates a model of physical constraints.

Related Experiment Videos

  • Utilizing quadratic objective functions within the MPC framework.

    • Main Results:

    • The anti-wind-up bumpless transfer controller is shown to be an inherent outcome of the MPC structure.
    • The proposed framework effectively manages actuator input limits.
    • Internal controller states are demonstrated to be well-updated under constrained operation.

    Conclusions:

    • Model Predictive Control with input constraints naturally yields anti-wind-up bumpless transfer capabilities.
    • The integrated physical constraint model enhances controller robustness and reliability.
    • The presented methodology offers a unified approach to advanced control design.