Title: A Model Based Approach for Sensor Fault Detection in Civil Aircraft Control Surface
Author(s): O. Sercekman, A.T. Kutay
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 715 - 729
Cite this article: Sercekman, O., Kutay, A.T., "A Model Based Approach for Sensor Fault Detection in Civil Aircraft Control Surface," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 715-729.
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Abstract: A model-based fault detection and diagnosis (FDD) solution improves the capability in a civil aircraft control surface whereas having low complexity and computational requirements. The main objective of the FDD. techniques that are extensively applied in industrial systems is to increase the sensitivity of fault detection scheme while maintaining a reliable system response with respect to additional unknown inputs. In the paper, a reformative approach to an observer-based fault detection method is introduced for FDD. As an effect of the stochastic attitude of the variables due to the noisy characteristics of some elements in the system and model uncertainties such as parametric uncertainty or unmodeled dynamics, false alarms are indicated and upon a new approach is practiced to attenuate the false alarm rates. The reliability of the available method is increased by choosing appropriate parameters with respect to the measurement noise and modelling errors. The designed fault detection model is integrated to a nonlinear civil aircraft model of Boeing 747 with a proper tuning of parameters. The system is developed in MATLAB Simulink and mainly consist of a closed-loop aircraft model to verify the effectiveness of the sensor fault detection technique, an observer to estimate the states of the aircraft during steady state flight, a fault indicator to propagate faulty responses to the system and a reconfigurator to identify the flight condition if it is fault-free or faulty by comparing the states which are achieved from the sensor of the control surface in real-time and provided from the flight control law computation. Fault detection is accomplished by evaluating any significant change in the behavior of the aircraft with respect to the fault-free behavior which is estimated by using a standard Kalman filter as an observer. The scheme presented based on Kalman filter composes a residual sensitive to fault incidents and maintains a reliable fault detection approach incororating the rejection of false alarm that is required for system reliability. The developed method is a viable solution for earlier control surface stuck detection to lower threshold amplitude as an outcome of multisimulation tests performed in MATLAB Simulink.