Fixed-time adaptive fuzzy command filtering control for a two-joint robotic manipulator with input dead zone...

Area of Science:

• Robotics
• Control Systems Engineering
• Artificial Intelligence

Background:

• Robotic manipulators face challenges like input dead zones, saturation, and time-varying delays.
• Traditional control methods struggle with these nonlinearities and delays, often requiring complex approximations.

Purpose of the Study:

• To develop an adaptive fuzzy fixed-time tracking control for a two-joint robotic manipulator.
• To address input deadzone saturation and time-varying delays without Pade approximation.

Main Methods:

• Utilized fuzzy logic systems as adaptive nonlinear approximators within a backstepping framework.
• Employed auxiliary signals to handle time-varying delays, avoiding Pade approximation.
• Introduced command filtering to mitigate the complexity explosion in backstepping.
• Approximated non-smooth nonlinearities using smooth functions and the mean-value theorem.

Main Results:

• Achieved fixed-time stability for the robotic manipulator system.
• Guaranteed boundedness of all closed-loop signals.
• Ensured tracking errors converge to a small neighborhood of zero within a fixed time.
• Demonstrated that convergence time is solely dependent on controller design parameters.

Conclusions:

• The proposed adaptive fuzzy control effectively manages nonlinearities and delays in robotic manipulators.
• The method provides precise tracking control with a predictable, fixed convergence time.
• Validated through simulation, confirming the practical applicability of the control strategy.