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

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.