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Adaptive passivity-based control extended for unknown control direction.

Juan C Travieso-Torres1, Camilo Contreras1, Francisco Hernández1

  • 1El Belloto 3735, Estación Central, Department of Industrial Technologies, Universidad de Santiago de, Chile.

ISA Transactions
|May 21, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a normalized adaptive passivity-based controller (NAPBC) for nonlinear systems with unknown control direction. The NAPBC offers improved performance and simpler tuning compared to existing methods.

Keywords:
Adaptive passivity-based controlConical tankNonlinear controlUnknown control direction

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Area of Science:

  • Control Systems Engineering
  • Nonlinear Dynamics
  • Adaptive Control Theory

Background:

  • Adaptive passivity-based controllers (APBC) are effective for nonlinear systems.
  • Handling unknown control direction in such systems is challenging.
  • Existing methods like Nussbaum gains can be complex with numerous parameters.

Purpose of the Study:

  • To propose a novel normalized adaptive passivity-based controller (NAPBC).
  • To address nonlinear systems with unknown control direction and parameters.
  • To offer a simpler and more parameter-efficient alternative to existing controllers.

Main Methods:

  • Design of a normalized adaptive passivity-based controller (NAPBC).
  • Development of a straightforward method to handle unknown control direction.
  • Stability analysis and proof for the controlled nonlinear system.
  • Expansion of tuning methods for normalized gains (fixed or time-varying).

Main Results:

  • The proposed NAPBC effectively manages unknown control direction with fewer parameters.
  • Stability of the closed-loop system is rigorously proven.
  • The NAPBC demonstrates superior performance over existing methods in experimental trials.
  • Improved performance indexes including ISI, Ess, MO, IAE, and Ts were observed.

Conclusions:

  • The NAPBC is a robust and efficient control strategy for nonlinear systems.
  • It simplifies the control design process by reducing parameter dependency.
  • The method shows significant practical applicability, as demonstrated on a conical tank pilot plant.