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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fault detection and diagnosis of aircraft actuators using fuzzy-tuning IMM filter


    Contributors:


    Publication date :

    2008-07-01


    Size :

    3266513 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Fault Diagnosis of Aircraft Actuators Based on AdaBoost-ASVM

    Wei, Ruonan / Jiang, Ju / Xu, Haiyan et al. | TIBKAT | 2022


    Fault Diagnosis of Aircraft Actuators Based on AdaBoost-ASVM

    Wei, Ruonan / Jiang, Ju / Xu, Haiyan et al. | Springer Verlag | 2021


    Fault Diagnosis and Condition Monitoring of Aircraft Electro-Mechanical Actuators

    Mazzoleni, Mirko / Di Rito, Gianpietro / Previdi, Fabio | Springer Verlag | 2021