Sensor FDI and reconfiguration in B-747 aircraft flight control system

Guven A., Hajiyev C.

INTERNATIONAL JOURNAL OF SUSTAINABLE AVIATION, vol.8, no.4, pp.312-335, 2022 (ESCI) identifier

  • Publication Type: Article / Article
  • Volume: 8 Issue: 4
  • Publication Date: 2022
  • Journal Indexes: Emerging Sources Citation Index (ESCI)
  • Page Numbers: pp.312-335
  • Keywords: sensor fault detection, lateral states estimation, electronic flight control systems, optimal linear Kalman filter, OLKF, reconfigured Kalman filter, state space models
  • Istanbul Technical University Affiliated: Yes


Recent research pay attention to sensor fault detection, isolation (FDI) and accommodation for flight safety of both civil and military aircraft. This study purposes to have estimation results of the lateral states that are close to real values even if there are faults on the lateral sensors of the Boeing-747 aircraft via optimal linear Kalman filter (OLKF) and reconfigurable Kalman filter (RKF). Single and double sensor faults are implemented on Boeing-747 aircraft model in steady state. In nominal case, the OLKF gives fine estimation results. However, if a malfunction on the measurement channels exists, the accuracy of estimations becomes poor. Single continuous bias sensor fault and measurement noise increment double sensor faults are implemented. The fault is detected, isolated and accommodated. Accuracy of the RKF is measured by root mean square error and it is proven that the estimation results are closer to actual values and gathered firmly.