This paper deals with the fault detection and estimation scheme for a class of nonlinear systems. An adaptive observer is designed where the unknown nonlinear term can be approximated and the fault is estimated based on radial basis function (RBF) neural network, respectively. The stability of the designed observer is also proved. Finally, simulation results based on an aircraft are presented to evaluate the performance of the proposed observer and the effectiveness of the fault estimation.
Fault detection and estimation for a class of nonlinear systems based on neural network observer
2016-08-01
268001 byte
Conference paper
Electronic Resource
English
Observer based fault detection in nonlinear systems
TIBKAT | 2010
|Unknown Input Observer Based Fault Class Isolation and Estimation
Tema Archive | 2010
|British Library Online Contents | 2002
|Fault Estimation Observer Design of Nonlinear Systems with Actuator Faults
Springer Verlag | 2017
|Fault Detection and Diagnosis Method Based on Sliding Mode-Neural Network Observer
British Library Online Contents | 2003
|