ADAPTIVE NEURO-FUZZY BASED CONTROL SURFACE FAULT DETECTION AND RECONFIGURATION

Savanur, Shobha. R and Kashyap, SK (2008) ADAPTIVE NEURO-FUZZY BASED CONTROL SURFACE FAULT DETECTION AND RECONFIGURATION. In: International Conference on Aerospace Science and Technology (INCAST 2008-094), 26-28 Jun 2008, Bangalore, India.

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    Abstract

    The aircraft becomes unstable due to fault in actuator or if there is a loss of control surface effectiveness due to damaged or blown surfaces. One of the popular methods to detect and reconfigure the surface fault is model based approach e.g. Extended Kalman filter (EKF). Using EKF, the parameters of control distribution matrix are estimated as augmented states of the system which are subsequently used to compute feedback gain to reconfigure the impaired system In this paper, detection and reconfiguration of surface fault in elevator of an aircraft is demonstrated using Adaptive Neuro - Fuzzy Inference System ANFIS . Under this approach, i) ANFIS is trained using time history of i/o data i.e. inputs as errors between nominal (healthy) states of aircraft and its faulty states (noise free) for different fault conditions and output as parameters of control distribution matrix and ii) trained ANFIS is subsequently used to estimate the parameters of control distribution matrix for the actual fault condition and the reconfiguration is carried out by computing new feedback gain using pseudo-inverse technique.

    Item Type: Conference or Workshop Item (Paper)
    Subjects: ENGINEERING > Communications and Radar
    Division/Department: Other, Flight Mechanics and Control Division
    Depositing User: Dr Sudesh Kumar Kashyap
    Date Deposited: 30 Jun 2010 09:50
    Last Modified: 30 Jun 2010 09:50
    URI: http://nal-ir.nal.res.in/id/eprint/8469

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