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Related Experiment Video

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Switching Adaptive Control with Applications on Robot Manipulators.

Shihao Wang1, Shiqi Zheng1, Yushu Deng2

  • 1School of Automation, China University of Geosciences, Wuhan 430074, China.

Entropy (Basel, Switzerland)
|July 8, 2023
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Summary
This summary is machine-generated.

This study introduces novel logic-based switching adaptive control methods for nonlinear systems. These controllers achieve finite-time and exponential stability, even with unknown system parameters and control directions, simplifying complex control designs.

Keywords:
adaptive controlfinite-time controllogic-based switchingsampled-data control

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Area of Science:

  • Control Theory
  • Nonlinear Systems
  • Adaptive Control

Background:

  • Existing adaptive control methods often struggle with fully unknown nonlinearities and control directions.
  • Sampled-data control for nonlinear systems with uncertain growth rates presents significant challenges.

Purpose of the Study:

  • To develop a new logic-based switching adaptive control method for finite-time stabilization of nonlinear systems.
  • To investigate sampled-data control for nonlinear systems with uncertain linear growth rates, enabling adaptive parameter and sampling time adjustments.

Main Methods:

  • Utilizing the adding a barrier power integrator technique for finite-time stabilization.
  • Proposing a new logic-based switching mechanism for sampled-data control systems.
  • Developing adaptive control strategies for uncertain parameters and sampling times.

Main Results:

  • Achieved finite-time stability for nonlinear systems with fully unknown nonlinearities and unknown control direction.
  • Demonstrated exponential stability for sampled-data nonlinear systems with uncertain linear growth rates.
  • Controller structures are simplified, avoiding approximation methods like neural networks or fuzzy logic.

Conclusions:

  • The proposed logic-based switching adaptive control methods offer robust and simplified solutions for challenging nonlinear systems.
  • The techniques are validated through applications in robot manipulator control, showing practical applicability.