Fault Reconstruction Algorithm for Fractional-Order Nonlinear Switching Systems Based on Optimal Fault-Tolerant
IEEE Transactions on Cybernetics
|August 19, 2024
Summary
This study presents novel fault reconstruction algorithms for fractional-order nonlinear switching systems (FONSSs). The developed method ensures system stability and fault compensation using adaptive control and neural networks.
Area of Science:
- Control Systems Engineering
- Nonlinear Dynamics
- Fault Diagnosis and Tolerance
Background:
- Fractional-order nonlinear systems (FONSSs) are susceptible to actuator and sensor faults.
- Existing fault reconstruction methods may face challenges with transient stability during system switching.
Purpose of the Study:
- To develop novel fault reconstruction algorithms for FONSSs.
- To address actuator and sensor faults in these systems.
- To enhance system stability and fault tolerance.
Main Methods:
- Transformation of the faulted FONSS into fast and slow subsystems using global differential homogeneous transformation.
- Integration of persistent dwell-time (PDT) switching in observer design to ensure stability.
- Design of an optimal adaptive fault-tolerant control strategy using actor-critic neural networks (NN).
Main Results:
- Successfully reconstructed faults in FONSSs.
- Achieved stability of error dynamics in fast and slow subsystems.
- Demonstrated effective fault compensation through simulation.
Conclusions:
- The proposed fault reconstruction algorithms and adaptive fault-tolerant control strategy are effective for FONSSs.
- The integration of PDT switching and NN-based control offers a robust solution for systems with faults.
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