This paper proposes a new interacting multiple model (IMM) filter for actuator fault detection. Since each individual filter of the IMM filter uses the combined information of the estimation values from all the operating filters, it can effectively estimate system parameter variations, thereby it can diagnose the actuator damage with an unknown magnitude. In this study, to diagnose the actuator failure fast and accurately, fuzzy logic is used to tune a transition probability among multiple models. This makes the fault detection process smooth and reduces the possibility of false fault detection. Also, a discrete fault tolerant command tracker is derived to cope with actuator damages. To validate the performance of the proposed fault detection and diagnosis (FDD) algorithm, numerical simulations are performed for a high performance aircraft system.
Fault detection and diagnosis of aircraft actuators using fuzzy-tuning IMM filter
IEEE Transactions on Aerospace and Electronic Systems ; 44 , 3 ; 940-952
2008-07-01
3266513 byte
Article (Journal)
Electronic Resource
English
Fault Detection and Diagnosis of Aircraft Actuators using Fuzzy-Tuning IMM Filter
Online Contents | 2008
|Fault diagnosis of electromechanical actuators using a neuro-fuzzy network
Tema Archive | 1995
|Fault Diagnosis of Aircraft Actuators Based on AdaBoost-ASVM
TIBKAT | 2022
|Fault Diagnosis of Aircraft Actuators Based on AdaBoost-ASVM
Springer Verlag | 2021
|Fault Diagnosis and Condition Monitoring of Aircraft Electro-Mechanical Actuators
Springer Verlag | 2021
|