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A Digitalized Gyroscope System Based on a Modified Adaptive Control Method.

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This study demonstrates an adaptive control algorithm for Micro-Electro-Mechanical System (MEMS) gyroscopes. The method enables online parameter estimation and robust control, validated through simulations and FPGA implementation for angular rate sensing.

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Area of Science:

  • Engineering
  • Control Systems
  • Micro-Electro-Mechanical Systems (MEMS)

Background:

  • MEMS gyroscopes are crucial for angular rate sensing.
  • Traditional control methods face challenges with parameter variations and coupling effects.

Purpose of the Study:

  • To investigate the application of an adaptive control algorithm to MEMS gyroscopes.
  • To enhance the performance and stability of MEMS gyroscopes through online parameter estimation and adaptive control.

Main Methods:

  • Implemented an adaptive control algorithm using phase-locked loops (PLLs) for steady amplitude and frequency control.
  • Modified the adaptive law to account for unequal coupling stiffness and damping.
  • Incorporated a rotation elimination section and utilized Lyapunov criterion for stability analysis.
  • Validated the algorithm via simulations and Field Programmable Gate Array (FPGA) implementation.

Main Results:

  • The adaptive control algorithm successfully estimated key gyroscope parameters online.
  • Coupling components were effectively detected and suppressed.
  • Simulations and hardware implementation confirmed the algorithm's feasibility and accuracy.
  • Repeated experiments with multiple gyroscopes demonstrated the algorithm's commonality.

Conclusions:

  • The modified adaptive control algorithm is a feasible and effective approach for MEMS gyroscopes.
  • The digital implementation on FPGA provides a robust solution for angular rate sensing.
  • The algorithm offers improved performance and stability in MEMS gyroscope systems.