Adaptive Approximation Tracking Control of a Continuum Robot With Uncertainty Disturbances

Area of Science:

• Robotics
• Control Systems Engineering

Background:

• Continuum robots offer inherent compliance and safety, making them suitable for human-robot interaction and medical surgery.
• Controlling continuum robots is challenging due to complex nonlinearities, parameter uncertainties, and external disturbances.

Purpose of the Study:

• To develop a novel adaptive control scheme for continuum robots to overcome challenges posed by uncertain dynamics and unknown external disturbances.
• To introduce an adaptive function approximation technique (FAT) control strategy with no update laws for robust performance.

Main Methods:

• The proposed adaptive FAT control (AFATC) strategy utilizes function approximation techniques (FAT) to express the control law.
• The control law is formulated as a finite linear combination of orthogonal basis functions, employing a fixed control structure without time-varying weight matrices.
• Controller stability is rigorously proven using Lyapunov functions.

Main Results:

• Simulation results demonstrate that the proposed AFATC scheme achieves superior control performance compared to the regressor-free adaptive control (RFAC) method.
• The effectiveness of the AFATC scheme was validated through real-time experimental demonstrations.

Conclusions:

• The novel adaptive FAT control scheme provides a robust and effective solution for controlling continuum robots in the presence of uncertainties.
• The AFATC strategy offers significant advantages in enhancing the performance and reliability of continuum robots for practical applications.