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Predictive ESO-based control with guaranteed stability for uncertain MIMO constrained systems.

Alberto Castillo1, Tito L M Santos2, Pedro Garcia1

  • 1Instituto de Automática e Informática Industrial, Universitat Politècnica de València, Valencia, Spain.

ISA Transactions
|January 4, 2021
PubMed
Summary
This summary is machine-generated.

A new predictive controller using Extended State Observers (ESO) guarantees stability for complex systems. This innovation improves control accuracy and reliability in applications like diabetes management.

Keywords:
Constrained systemsExtended State Observer (ESO)Predictive controlUncertain systems

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Area of Science:

  • Control Systems Engineering
  • Biomedical Engineering
  • Systems Theory

Background:

  • Predictive controllers utilizing Extended State Observers (ESO) are increasingly adopted for managing complex systems.
  • A significant challenge with current ESO-based predictive controllers is the lack of guaranteed closed-loop stability.
  • Existing formulations often fail to provide strict stability assurances, limiting their application.

Purpose of the Study:

  • To develop a novel discrete predictive controller based on Extended State Observer (ESO) with guaranteed input-to-state stability.
  • To address the critical issue of closed-loop stability in ESO-based predictive control structures.
  • To demonstrate the practical advantages of the proposed controller through a relevant simulation case study.

Main Methods:

  • Development of a predictive Extended State Observer (ESO)-based discrete controller.
  • Inclusion of two fixed terms in the cost-index definition to ensure input-to-state stability.
  • Validation via a simulation case study focusing on glucose control in type-1 diabetes patients.

Main Results:

  • A novel predictive ESO-based discrete controller with guaranteed input-to-state stability was successfully developed.
  • The proposed controller construction method ensures stability under standard ESO assumptions.
  • The simulation results demonstrated the effectiveness and advantages of the new control structure.

Conclusions:

  • The developed predictive ESO-based controller offers guaranteed input-to-state stability, overcoming limitations of previous methods.
  • This approach provides a robust solution for regulating MIMO systems with disturbances, uncertainties, and actuator constraints.
  • The controller shows significant potential for applications such as artificial pancreas systems for type-1 diabetes management.