A barrier function-based fixed-time fractional order sliding mode super-twisting control for robotic manipulators...

Area of Science:

• Robotics
• Control Theory
• Nonlinear Systems

Background:

• Robotic manipulators face performance degradation due to uncertainties, chattering, and actuator faults.
• Existing control methods often require disturbance observers or constant bounds for fault information.

Purpose of the Study:

• To propose a fractional fixed-time super-twisting control scheme for robotic manipulators.
• To address uncertainties and actuator faults without relying on disturbance observers.
• To enhance convergence speed and robustness.

Main Methods:

• Construction of a novel fractional-order sliding manifold for accelerated convergence.
• Introduction of a modified super-twisting algorithm (STA) with a higher-order correction term to mitigate chattering.
• Development of an adjustable barrier function (ABF) to relax bounds on fault information and disturbances.

Main Results:

• Achieved accelerated convergence using the fractional-order sliding manifold.
• Mitigated chattering and improved convergence speed with the modified STA.
• Demonstrated robustness and effectiveness through numerical simulations and validations.

Conclusions:

• The proposed fractional fixed-time super-twisting control scheme effectively handles uncertainties and faults in robotic manipulators.
• The strategy guarantees fixed-time convergence and enhanced performance without disturbance observers.
• The adjustable barrier function offers flexibility in managing fault information and disturbances.