Adaptive Neuro-Fuzzy Based Sensor Fault Detection, Isolation and Reconfiguration

Savanur, Shobha R. and Kashyap, SK and Raol, JR (2008) Adaptive Neuro-Fuzzy Based Sensor Fault Detection, Isolation and Reconfiguration. Journal of Systems Science and Engineering, System Society of India, 17 (1). ISSN 0972-5032

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    Abstract

    Sensor fault detection is generally performed by estimating the states of plant and comparing them with measured values. A fault is detected when the difference between the estimated and measured values crosses a threshold value. In this paper, an approach to detect and isolate the sensor fault affecting the mean of the Kalman filter innovation sequence is presented. Reconfiguration for sensor faults is carried out using two methods viz., i) by replacing faulty sensor by an extra healthy sensor(hardware redundancy) and ii) by ignoring measurement from faulty sensor(analytical redundancy). Also the sensor fault detection, isolation and reconfiguration is demonstrated using Adaptive-Neuro Fuzzy Inference System (ANFIS) -a non model based approach. In this paper, the longitudinal dynamics of an aircraft control system are considered and the detection and isolation of sensor faults affecting mean of the innovation sequence are studied. Reconfiguration for sensor faults is carried out so that the estimator provides the controller with an accurate estimate of the system state after the sensor fault.

    Item Type: Journal Article
    Subjects: AERONAUTICS > Aircraft Stability and Control
    Division/Department: Other, Flight Mechanics and Control Division, Flight Mechanics and Control Division
    Depositing User: Dr Sudesh Kumar Kashyap
    Date Deposited: 29 Jun 2010 12:17
    Last Modified: 29 Jun 2010 12:17
    URI: http://nal-ir.nal.res.in/id/eprint/8457

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