Dealing with Fault Dynamics in Nonlinear Systems via Double Neural Network Units
Most fault detection and accommodation methods have traditionally been derived based on linear system modeling techniques, which restrict the type of practical failure situation that can be modeled. In this paper we explore a methodology for fault accommodation in nonlinear dynamic systems. A new control scheme is derived by incorporating two neural network (NN) units to effectively attenuate and compensate uncertain dynamics due to unpredictable faults. It is shown that the method is independent of the nature of the fault. Numerical simulations are included to demonstrate the effectiveness of the proposed method.
Unable to display preview. Download preview PDF.
- 1.Yang, H., Saif, M.: Fault Detection and Isolation for a Class of Nonlinear Systems Using an Adaptive Observer. In: Proc. Amer. Contr. Conf., pp. 463–467 (1997)Google Scholar
- 6.Borairi, M., Wang, H.: Actuator and Sensor Fault Diagnosis of Nonlinear Dynamic Systems via Genetic Neural Networks and Adaptive Parameter Estimation Technique. In: IEEE Intl. Conf. on Contr. App. (1998)Google Scholar
- 7.Wang, H.: Fault Detection and Diagnosis for Unknown Nonlinear Systems: a Generalized Framework via Neural Network. In: IEEE Intl. Conf. On Intelligent Processing Sys., pp. 1506–1510 (1997)Google Scholar