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Stabilization and synchronization for a mechanical system via adaptive sliding mode control.

Zhankui Song1, Kaibiao Sun2, Shuai Ling1

  • 1School of Information Science and Engineering, Dalian Polytechnic University, Dalian 116034, China.

ISA Transactions
|March 11, 2017
PubMed
Summary

This study addresses chaotic centrifugal flywheel governor synchronization challenges. A novel control law effectively suppresses disturbances and compensates for parameter uncertainties, ensuring system stability and accurate tracking.

Keywords:
Adaptive controlNon-autonomous centrifugal governorSliding mode controlSynchronization tracking

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Area of Science:

  • Control Systems Engineering
  • Nonlinear Dynamics
  • Mechanical Engineering

Background:

  • Centrifugal flywheel governors are critical in regulating engine speed.
  • Synchronization of chaotic systems presents significant control challenges.
  • Underactuated systems require advanced control strategies for precise tracking.

Purpose of the Study:

  • To investigate and solve the synchronization problem for chaotic centrifugal flywheel governors.
  • To develop a robust control strategy for systems with parameter uncertainty and lumped disturbances.
  • To ensure a slave governor system accurately follows a master governor system.

Main Methods:

  • Sliding mode control strategy combined with Nussbaum gain technique.
  • Development of adaptation updating algorithms based on Lyapunov stability analysis.
  • Modeling the slave centrifugal flywheel governor as an underactuated following-system.

Main Results:

  • A novel synchronization control law was successfully developed.
  • Lumped disturbances were effectively suppressed.
  • Adverse effects of parameter uncertainties were compensated, ensuring stability.
  • Synchronization tracking errors were proven to converge near the origin.

Conclusions:

  • The proposed control scheme demonstrates high effectiveness in synchronizing chaotic centrifugal flywheel governors.
  • The method provides robust performance against parameter uncertainties and lumped disturbances.
  • This research contributes a reliable control solution for complex governor systems.