Adaptive controller based on barrier Lyapunov function for a composite Cartesian-delta robotic device for precise...

Area of Science:

• Robotics
• Control Systems Engineering
• Mechatronics

Background:

• Composite robotic devices, combining Cartesian and Delta robots, present complex trajectory tracking challenges.
• Existing control methods often struggle with modeling uncertainties, external perturbations, and strict state constraints.
• Ensuring robust and precise motion control is critical for advanced robotic applications.

Purpose of the Study:

• To design and evaluate an adaptive event-driven controller for a composite robotic device.
• To address trajectory tracking problems under modeling uncertainties and external perturbations.
• To guarantee satisfaction of state constraints using barrier Lyapunov functions and adaptive gains.

Main Methods:

• Development of an adaptive event-driven control strategy for a composite Cartesian-Delta robot system.
• Utilizing barrier Lyapunov functions to enforce state constraints and ensure ultimate boundedness of tracking errors.
• Implementing a time-varying adaptive gain to manage uncertainties and perturbations.
• Employing an event-driven approach based on robot movement within predefined zones.

Main Results:

• The proposed adaptive barrier control demonstrated superior trajectory tracking performance compared to traditional linear state feedback controllers.
• The controller successfully satisfied predefined state constraints throughout the operation.
• Analysis of mean square error confirmed the effectiveness and benefits of the adaptive barrier control strategy.

Conclusions:

• The adaptive event-driven controller offers a robust solution for trajectory tracking in composite robotic systems.
• Barrier Lyapunov functions are effective in managing state constraints under dynamic perturbations.
• The developed control approach enhances robotic system precision and stability, outperforming conventional methods.