Nonlinear Observer-Based Visual Servoing and Vibration Control of Flexible Robotic Manipulators With a Fixed Camera

Area of Science:

• Robotics and Control Systems
• Mechatronics
• Applied Mathematics

Background:

• Flexible manipulators present control challenges due to their infinite-dimensional nature and unmeasurable states.
• Visual servoing offers a promising approach for robot control, but typically requires accurate system state information.
• Vibration suppression is critical for precise motion control of lightweight robotic systems.

Purpose of the Study:

• To develop a visual servoing and vibration suppression control strategy for flexible manipulators with unmeasurable states.
• To enable control using only image feedback, simplifying implementation and reducing sensor requirements.
• To simultaneously regulate feature point positions and dampen manipulator vibrations.

Main Methods:

• Decomposition of manipulator dynamics into slow and fast subsystems using singular perturbation theory.
• Design of nonlinear observers, utilizing Lie derivatives, for simultaneous estimation of system states and unknown camera parameters.
• Image-based controller design for slow and fast subsystems using estimated states.
• Stability analysis using Lyapunov theory.

Main Results:

• Simultaneous regulation of image feature point positions and suppression of flexible manipulator vibrations.
• Successful estimation of unmeasurable system states and unknown camera intrinsic parameters.
• Demonstration of control effectiveness through experimental results on a flexible single-link manipulator.
• Validation of the proposed control scheme's stability.

Conclusions:

• The proposed image-based control approach effectively addresses visual servoing and vibration suppression for flexible manipulators.
• The method simplifies controller implementation by relying solely on visual feedback.
• The approach is robust and stable, as proven by Lyapunov theory and experimental validation.