Fault diagnosis in dynamic systems: theory and application
Fault diagnosis in dynamic systems: theory and application
Nonlinear control design: geometric, adaptive and robust
Nonlinear control design: geometric, adaptive and robust
Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Fault diagnosis for nonlinear systems using a bank of neural estimators
Computers in Industry - Special issue: Soft computing in industrial applications
Issues of Fault Diagnosis for Dynamic Systems
Issues of Fault Diagnosis for Dynamic Systems
Observers for Takagi-Sugeno fuzzy systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On fuzzy logic applications for automatic control, supervision, and fault diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Output Tracking Control for Fuzzy Systems Via Output Feedback Design
IEEE Transactions on Fuzzy Systems
Sliding mode observers for fault detection and isolation
Automatica (Journal of IFAC)
Brief Sliding mode observers for detection and reconstruction of sensor faults
Automatica (Journal of IFAC)
Nonlinear system fault diagnosis based on adaptive estimation
Automatica (Journal of IFAC)
Automated fault diagnosis in nonlinear multivariable systems using a learning methodology
IEEE Transactions on Neural Networks
A stable neural network-based observer with application to flexible-joint manipulators
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
A robust fault diagnosis (FD) scheme using Takagi-Sugeno (T-S) neural-fuzzy model and sliding mode technique is presented for a class of nonlinear systems that can be described by T-S fuzzy models. A neural-fuzzy observer and neural-fuzzy sliding mode observer are constructed respectively. A modified back-propagation (BP) algorithm is used to update the parameters of the two observers. Stability of the observers are analyzed as well. Finally, the proposed FD scheme using these observers is applied to a point mass satellite orbital control system example. Numerical simulation results show that this robust fault diagnosis strategy is effective for the considered class of nonlinear systems.