Adaptive constraint-following control for maintenance robotic manipulator with uncertainties

Area of Science:

• Robotics
• Control Systems Engineering
• Mechanical Engineering

Background:

• Maintenance robotic manipulator systems for armored vehicles require high reliability and motion stability.
• Parameter uncertainties and external disturbances pose significant challenges to existing control methodologies.

Purpose of the Study:

• To propose a novel adaptive robust control methodology for enhancing the performance of maintenance robotic manipulator systems.
• To address parameter uncertainties and external disturbances in robotic manipulator control.

Main Methods:

• Utilized the Udwadia-Kalaba (UK) dynamic framework for system modeling.
• Integrated a leakage mechanism into the adaptive law to manage parameter growth and control gain.
• Employed co-simulation in a multibody dynamics environment for validation.

Main Results:

• The proposed adaptive law suppresses unbounded parameter growth under continuous disturbances.
• The controller automatically attenuates control gain upon error convergence, improving transient response smoothness.
• Effectiveness of the controller was validated through co-simulation.

Conclusions:

• The novel adaptive robust control methodology enhances reliability and motion stability of robotic manipulators for armored vehicles.
• The integrated leakage mechanism effectively addresses system uncertainties and disturbances.
• The Udwadia-Kalaba dynamic framework provides a robust foundation for developing advanced robotic control systems.