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Related Experiment Video

Updated: Jul 6, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

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Adaptive sliding-mode control for nonlinear systems with uncertain parameters.

Ying-Jeh Huang1, Tzu-Chun Kuo, Shin-Hung Chang

  • 1Department of Electrical Engineering, Yuan Ze University, Chung-Li, Taiwan, R.O.C. eejyh@saturn.yzu.edu.tw

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|March 20, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a novel adaptive sliding-mode controller for robustly managing nonlinear systems with unknown parameters. The adaptive tuning method ensures reliable tracking and stability without needing to know uncertainty bounds, proving effective in experiments.

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Area of Science:

  • Control Engineering
  • Nonlinear System Dynamics
  • Adaptive Control Theory

Background:

  • Nonlinear systems often exhibit parameter uncertainties, posing challenges for robust control.
  • Traditional sliding-mode controllers can suffer from high-frequency switching, leading to undesirable chattering.
  • Existing methods may require prior knowledge of uncertainty bounds, limiting practical application.

Purpose of the Study:

  • To develop a systematic adaptive sliding-mode controller for robust control of nonlinear systems.
  • To address unknown but bounded system uncertainties without high-frequency switching.
  • To guarantee tracking performance and system stability using Lyapunov theory.

Main Methods:

  • A novel adaptive tuning approach is proposed, eliminating the need for high-frequency switching.
  • The controller design systematically handles unknown parameter uncertainties.
  • Lyapunov theory is employed to rigorously prove system robustness and stability.

Main Results:

  • The proposed controller guarantees robust tracking performance for nonlinear systems.
  • System stability is mathematically proven using Lyapunov functions.
  • The method effectively manages uncertainties without requiring knowledge of their upper bounds.

Conclusions:

  • The developed adaptive sliding-mode controller offers a robust and effective solution for nonlinear systems with uncertainties.
  • The absence of high-frequency switching and prior knowledge of uncertainty bounds enhances practical implementation.
  • Experimental validation confirms the efficacy of the proposed control strategy.