Adaptive fixed-time fault-tolerant trajectory tracking control for disturbed robotic manipulator

Area of Science:

• Robotics
• Control Systems Engineering
• Mechatronics

Background:

• Robotic manipulators require precise trajectory control, which is challenged by external disturbances, actuator faults, and system uncertainties.
• Existing control methods often struggle with singularity issues and may require boundary layers, complicating implementation.
• Ensuring robust and rapid convergence in robotic control systems remains a significant research objective.

Purpose of the Study:

• To introduce a novel fixed-time trajectory control method for robotic manipulators.
• To enhance trajectory precision and robustness against disturbances, faults, and uncertainties.
• To develop a continuous adaptive control strategy that mitigates chattering.

Main Methods:

• Utilized a fast fixed-time nonsingular terminal sliding surface (FFNTSS) for bounded convergence independent of initial conditions.
• Developed a continuous adaptive fixed-time nonsingular terminal sliding mode fault-tolerant control (CAFNTSMFTC) based on FFNTSS and adaptive methodology.
• Employed Lyapunov theorem for rigorous analysis of system stability and convergence of sliding mode variables and tracking errors.

Main Results:

• Demonstrated fixed-time convergence of sliding mode variables and tracking errors to a small neighborhood of the origin.
• The CAFNTSMFTC approach eliminates the need for a boundary layer by approximating the uncertainty's upper bound.
• Simulations on the PUMA560 robot validated precise trajectory tracking and fast convergence under various fault and uncertainty conditions.

Conclusions:

• The proposed CAFNTSMFTC strategy offers superior performance in robotic manipulator trajectory control.
• The method ensures fixed-time convergence and robustness against significant system challenges.
• The continuous nature of the control strategy effectively mitigates undesirable chattering phenomena.