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Second-order integral sliding-mode control with experimental application.

Murat Furat1, İlyas Eker2

  • 1Mustafa Kemal University, Department of Electrical & Electronic Engineering, 31200 Hatay, Turkey.

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|July 10, 2014
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Summary

A new second-order sliding-mode controller effectively manages uncertain real systems despite model approximations. This robust control method minimizes chattering for reliable, long-term performance in practical applications.

Keywords:
Adaptive gainIntegral sliding-modeStability

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Area of Science:

  • Control Systems Engineering
  • Robotics and Automation
  • Nonlinear Control Theory

Background:

  • Real-world systems often exhibit uncertainties and external disturbances.
  • Existing control strategies may struggle with model inaccuracies and performance degradation.
  • Chattering is a common issue in sliding-mode control, limiting practical application.

Purpose of the Study:

  • To propose a novel second-order sliding-mode controller for single-input single-output (SISO) uncertain systems.
  • To demonstrate the controller's ability to overcome uncertainties and disturbances using an approximate model.
  • To reduce the chattering phenomenon for enhanced practical usability.

Main Methods:

  • Design of a second-order sliding-mode controller incorporating an integral-type sliding surface.
  • Utilization of Lyapunov stability theorem to rigorously prove stability and robustness.
  • Implementation of a switching gain strategy with known system parameters to mitigate chattering.

Main Results:

  • The proposed controller successfully compensates for system uncertainties and external load disturbances.
  • Stability and robustness are mathematically proven via Lyapunov stability theorem.
  • Significant reduction in chattering phenomenon observed, enhancing suitability for real-time applications.

Conclusions:

  • The developed second-order sliding-mode controller offers a robust and stable solution for uncertain SISO systems.
  • The controller's effectiveness is validated through real-system experiments, outperforming existing methods.
  • The proposed approach is suitable for long-term deployment in practical engineering scenarios.