Sensor Fault Detection, Isolation, and Accommodation Applied to B-747

Optimal linear Kalman filter, fault detection, fault isolation, and reconfigurable Kalman filter algorithms have been applied to the lateral dynamics of Boeing-747 aircraft in this study. The flight dynamic model of Boeing-747 aircraft in steady-state flight condition is presented and investigated. In nominal case, the OLKF gives fine estimation values. However, when there is a malfunction on the measurement channels, the accuracy of the filter estimations becomes poor, and the filter becomes unreliable. Two faulty cases took place on the system. The first sensor fault is the single-sensor fault, and the second is a simultaneous double-sensor fault. The fault detection algorithm detects the fault, and isolation process ran and calculate the statistics of the rate of sample and theoretical error variances. For fault accommodation process, this chapter presents reconfigurable Kalman filter algorithm to enhance the estimation values of the filter.