Adaptive nonsingular fixed-time sliding mode control for uncertain robotic manipulators under actuator saturation

Area of Science:

• Robotics
• Control Theory
• Mechatronics

Background:

• Robotic manipulators face challenges like external disturbances, inertia uncertainties, and actuator saturation.
• Existing control methods may suffer from singularities, slow convergence, or require prior knowledge of uncertainty bounds.

Purpose of the Study:

• To develop an adaptive nonsingular fixed-time sliding mode control (ANFSMC) for robotic manipulators.
• To ensure global approximate fixed-time convergence under external disturbances and inertia uncertainties.
• To address actuator saturation while minimizing tracking errors and energy consumption.

Main Methods:

• Proposed a novel nonsingular fixed-time sliding mode control (NFSMC) to avoid singularities and ensure rapid convergence.
• Developed an adaptive NFSMC (ANFSMC) that does not require prior knowledge of uncertainty bounds.
• Designed an actuator saturation compensator to reduce chattering and enhance trajectory tracking.
• Utilized Lyapunov stability theory for system analysis.

Main Results:

• The ANFSMC achieves global approximate fixed-time convergence for robotic manipulators.
• The controller demonstrates small absolute tracking errors and low energy consumption.
• Actuator saturation is effectively compensated, reducing system chattering.
• Numerical simulations validate the effectiveness and superiority of the proposed schemes.

Conclusions:

• The ANFSMC scheme provides robust and efficient trajectory tracking for robotic manipulators.
• The adaptive nature and singularity-free design offer significant advantages over conventional methods.
• The controller is well-suited for applications requiring precise and fast robotic motion under uncertain conditions.