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Computational Efficiency-Based Adaptive Tracking Control for Robotic Manipulators with Unknown Input Bouc-Wen

Kan Xie1,2, Yue Lai3,4, Weijun Li5,6

  • 1School of Automation, Guangdong University of Technology, Guangzhou 510006, China. kanxiegdut@gmail.com.

Sensors (Basel, Switzerland)
|June 23, 2019
PubMed
Summary

This study introduces an adaptive control method for robotic manipulators to manage unknown Bouc-Wen hysteresis, improving tracking accuracy and computational efficiency for better performance.

Keywords:
adaptive controlcomputational efficiencyhysteresisrobotic manipulatorssensing and control

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Nonlinear Dynamics

Background:

  • Robotic manipulators require advanced controllers to handle closed-loop nonlinearities like input nonlinearities for optimal performance.
  • Real-time implementation necessitates computationally efficient control strategies.

Purpose of the Study:

  • To investigate the unknown input Bouc-Wen hysteresis control problem in robotic manipulators.
  • To develop an adaptive control scheme that enhances computational efficiency and tracking accuracy.

Main Methods:

  • Hysteresis dynamics modeled as an integrated control unit within the robotic manipulator system.
  • Adaptive control and a dynamical gain-based approach utilized.
  • Lyapunov theory employed for stability and effectiveness proofs.

Main Results:

  • Developed two adaptive parameters to enhance computational efficiency.
  • Achieved asymptotic tracking, an improvement over the ultimately bounded tracking errors in existing methods.
  • Demonstrated validity through numerical examples for fixed-point and trajectory controls.

Conclusions:

  • The proposed adaptive control method effectively addresses unknown input Bouc-Wen hysteresis in robotic manipulators.
  • Significant improvement in control quality and tracking performance is achieved.
  • The method offers a computationally efficient solution for real-time applications.