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Adaptive Fuzzy Sliding Mode Control for a Micro Gyroscope with Backstepping Controller.

Juntao Fei1, Yunmei Fang2, Zhuli Yuan2

  • 1College of IoT Engineering, Hohai University, Changzhou 213022, China.

Micromachines
|November 3, 2020
PubMed
Summary

This study introduces an adaptive backstepping fuzzy sliding control (ABFSC) for micro gyroscopes. The novel approach self-learns fuzzy parameters to enhance stability and performance against system nonlinearities and disturbances.

Keywords:
adaptive controlbackstepping approachmicro gyroscopetracking performance

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Area of Science:

  • Control Systems Engineering
  • Robotics
  • Mechatronics

Background:

  • Micro gyroscopes are critical for navigation and stabilization.
  • Traditional control methods struggle with inherent nonlinearities and external disturbances.
  • Adaptive control is needed for robust micro gyroscope performance.

Purpose of the Study:

  • To develop an adaptive backstepping fuzzy sliding control (ABFSC) for micro gyroscopes.
  • To enhance system stability and robustness against nonlinearities and parameter variations.
  • To enable self-learning capabilities for controller parameter adjustment.

Main Methods:

  • Utilizing a backstepping design methodology.
  • Implementing an adaptive fuzzy sliding mode control strategy.
  • Employing Lyapunov function analysis for stability verification.

Main Results:

  • The proposed ABFSC effectively rejects system nonlinearities.
  • The controller demonstrates self-learning ability for fuzzy parameter adaptation.
  • Simulations confirm robustness to external disturbances and parameter changes.
  • Satisfactory tracking and approximation performance were achieved.

Conclusions:

  • The adaptive backstepping fuzzy sliding control approach ensures micro gyroscope stability.
  • The self-learning fuzzy parameters allow adaptation to dynamic system changes.
  • This method offers a robust and effective control solution for micro gyroscopes without prior model knowledge.