Disturbance observer-based robust prescribed-time sliding mode tracking control for robotic manipulator systems:...

Area of Science:

• Robotics
• Control Systems Engineering
• Mechatronics

Background:

• Robotic manipulators require precise trajectory tracking for complex tasks.
• Uncertainties like parameter variations, friction, and external disturbances hinder accurate control.
• Existing methods often lack guaranteed convergence times or require detailed system knowledge.

Purpose of the Study:

• To develop a novel prescribed-time disturbance observer (PTDO) for estimating lumped uncertainties.
• To design a robust prescribed-time sliding mode control (RPTSMC) strategy utilizing the PTDO.
• To achieve guaranteed prescribed-time trajectory tracking for robotic manipulators.

Main Methods:

• A novel PTDO is designed to estimate lumped uncertainties without prior knowledge.
• An RPTSMC strategy is developed, integrating the PTDO for uncertainty compensation.
• Lyapunov stability analysis is rigorously applied to prove the stability of both PTDO and RPTSMC.

Main Results:

• The PTDO effectively estimates lumped uncertainties within a prescribed-time frame.
• The RPTSMC strategy ensures the robotic manipulator achieves prescribed-time trajectory tracking.
• Experimental validation on the Unitree Z1 robotic manipulator confirms the method's effectiveness.

Conclusions:

• The proposed PTDO and RPTSMC provide an effective solution for robotic manipulator trajectory tracking.
• The control scheme guarantees convergence within a specified time, outperforming existing methods.
• The approach is robust to various uncertainties and validated experimentally.