Soft-event-triggered dynamic damping adaptive fuzzy constraints EPH control for robot manipulator

Area of Science:

• Robotics
• Control Theory
• Artificial Intelligence

Background:

• Robot manipulators face challenges with model uncertainty and external disturbances.
• Existing control methods often struggle with communication burden and sampling failures.

Purpose of the Study:

• To propose a novel soft-event-triggered adaptive fuzzy output-constraints error-port Hamiltonian control for robot manipulators.
• To enhance tracking performance and system stability despite model uncertainties.

Main Methods:

• Development of a generalized desired Hamiltonian function for stability analysis.
• Design of a dynamic damping matrix to optimize tracking performance.
• Implementation of a soft-event-triggered mechanism to reduce communication load.
• Integration of adaptive fuzzy systems and disturbance estimation for uncertainty compensation.

Main Results:

• The proposed controller effectively handles model uncertainty and external disturbances.
• The soft-event-triggered mechanism reduces communication burden and prevents sampling failures.
• Experimental validation on a robot manipulator platform confirms the controller's effectiveness.

Conclusions:

• The developed error-port Hamiltonian control strategy offers a robust solution for robot manipulators with output constraints and model uncertainty.
• The integration of adaptive fuzzy logic and dynamic damping significantly improves control performance and communication efficiency.