Adaptive Fuzzy Controller Design for Uncertain Robotic Manipulators Subject to Nonlinear Dead Zone Inputs

Area of Science:

• Robotics
• Control Systems
• Fuzzy Logic

Background:

• Robotic manipulators often exhibit complex nonlinear dynamics.
• Dead zones in robotic systems introduce significant control challenges.
• Accurate modeling of unknown nonlinear functions is crucial for precise control.

Purpose of the Study:

• To develop an adaptive fuzzy control scheme for multi-degree robotic manipulators.
• To address the challenges posed by dead zones and unknown nonlinear functions.
• To ensure bounded system states and convergence of tracking errors.

Main Methods:

• Utilizing fuzzy logic systems to approximate unknown nonlinear dynamics.
• Employing an adaptive fuzzy technique to handle dead zones.
• Applying Lyapunov stability criterion to guarantee system performance.

Main Results:

• Demonstrated the approximation of unknown nonlinear functions and dead zones.
• Ensured all system states and signals remain within a bounded region.
• Achieved convergence of tracking errors to a small neighborhood of the origin.

Conclusions:

• The proposed adaptive fuzzy scheme effectively controls robotic manipulators with dead zones.
• The method ensures stability and accurate tracking performance.
• Simulation results confirm the practicality and effectiveness of the proposed control strategy.