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Jie Ling1, Zhao Feng1, Min Ming1

  • 1School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China.

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A new model reference adaptive integral resonant control (MRAIRC) offers superior precision motion control for nanopositioning platforms. This adaptive control effectively handles load uncertainties, outperforming standard integral resonant control (IRC).

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Area of Science:

  • Control Engineering
  • Nanotechnology
  • Robotics

Background:

  • Precision motion control is crucial for nanopositioning platforms.
  • Existing integral resonant control (IRC) struggles with dynamic load uncertainties.
  • Piezo-actuated systems require robust control for accurate operation.

Purpose of the Study:

  • To introduce a model reference adaptive integral resonant control (MRAIRC) scheme.
  • To enhance adaptive precision motion control for piezo-actuated nanopositioning platforms.
  • To address dynamic changes caused by load uncertainties.

Main Methods:

  • Designed a standard IRC based on a second-order system model.
  • Utilized the closed-loop system as a reference model for uncertainties.
  • Employed MIT rules for adaptive controller gain laws and offline tuning.
  • Proved system stability using Lyapunov stability analysis.

Main Results:

  • The proposed MRAIRC demonstrated superior performance compared to standard IRC.
  • MRAIRC significantly reduced tracking errors for raster scanning signals (5-20 Hz).
  • The control scheme effectively managed load variations from 0 to 1000 g.

Conclusions:

  • MRAIRC provides robust and adaptive precision motion control for nanopositioning systems.
  • The adaptive nature of MRAIRC overcomes limitations of fixed-gain IRC.
  • This approach enhances the reliability and accuracy of piezo-actuated platforms under varying loads.