An Intelligent Actuator Fault Reconstruction Scheme for Robotic Manipulators

Area of Science:

• Robotics
• Control Systems Engineering
• Fault Diagnosis

Background:

• Actuator faults in robotic manipulators pose significant challenges to system performance and safety.
• Accurate and timely fault reconstruction is crucial for effective fault-tolerant control strategies.
• Existing methods often rely on specific control laws or detailed system models, limiting their applicability.

Purpose of the Study:

• To develop an intelligent and fast approach for reconstructing actuator faults in robotic manipulators.
• To achieve precise fault reconstruction, minimizing reconstruction errors.
• To create a fault reconstruction scheme that is independent of control laws, actuator models, and fault characteristics.

Main Methods:

• Utilizing an observer-based technique for fault estimation.
• Employing Lyapunov stability analysis to guarantee finite-time convergence of reconstruction error.
• Validating the proposed scheme through comprehensive simulation and experimental studies.

Main Results:

• The developed observer technique enables precise reconstruction of actuator faults.
• Reconstruction errors are demonstrated to converge to zero in finite time via Lyapunov stability analysis.
• The proposed method achieves perfect reconstruction performance, characterized by both precision and speed.

Conclusions:

• The proposed observer-based scheme offers a robust and efficient solution for actuator fault reconstruction in robotic manipulators.
• A key advantage is its independence from control law, dynamic model, fault type, and time-profile.
• The validated performance underscores its potential for practical implementation in fault-tolerant robotic systems.