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An Adaptive Prescribed Performance Tracking Motion Control Methodology for Robotic Manipulators with Global

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This study introduces an adaptive position tracking control (APPTMC) for manipulators, ensuring precise operation. The novel approach enhances robot precision and robustness while reducing harmful chattering.

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Area of Science:

  • Robotics
  • Control Systems Engineering

Background:

  • Ensuring precise steady-state and dynamic attitude during robot operation is critical.
  • Existing control methods may face challenges with constrained systems and chattering.

Purpose of the Study:

  • To investigate and propose an adaptive position tracking control (APPTMC) for manipulators.
  • To enhance precision, robustness, and reduce chattering in robot control systems.

Main Methods:

  • Modified proportional-performance functions (PPFs) to manage position tracking errors within a performance domain.
  • A modified non-integer sliding mode control (NISMS) based on transformed errors for steady-state analysis and singularity elimination.
  • A fixed-time unsaturated second-order sliding mode observer (USOSMO) for lumped uncertainty estimation.
  • An adaptive sliding-mode terminal sliding controller with switching logic (ASTwCL) to address observer errors and chattering.

Main Results:

  • The proposed APPTMC effectively manages position tracking errors within a pre-designed domain.
  • The system demonstrates finite-time convergence, singularity elimination, and accurate uncertainty estimation.
  • Simulations confirm significant improvements in precision, robustness, and reduction of harmful chattering.

Conclusions:

  • The developed observer-based control solution achieves precise position control (PCP) in finite-time using Lyapunov stability.
  • The proposed APPTMC offers a robust and effective solution for manipulator control with enhanced performance metrics.