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This paper presents the implementation of flight path reconstruction (FPR) and wind estimation techniques applied to a high performance fighter aircraft. The analysis is carried out for the flight test data gathered and stored in a Crash Data Recorder (CDR). The data signals obtained from CDR are generally highly noisy, with frequent data drop outs and also with low sampling rate. The estimation technique applied for data reconstruction is the extended Kalman filtering (EKF). The reconstructed trajectories can be compared with the actual flight trajectories such that, in case of unavailability of data from other sources (e.g., digital flight control computer), the algorithm should be able to reconstruct the trajectories with the minimum set of data available from the CDR. Wind estimation along with the trajectory reconstruction can give better accuracy in airspeed as well as flow angles.

The major emphasis in Fault-Tolerant Flight Control (FTFC) System is towards Fault Detection and Diagnosis (FDD). FDD is used to isolate the aircraft’s fault and provides information for reconfiguration mechanisms to recover the system from a faulty state. In this paper, based on the classification of faults in actuators and sensors, FTFC system design methods are proposed while retaining the existing flight control system (FCS) architecture. Fault scenarios broadly can be classified as one that can be identified and addressed using a sensor or actuator redundancy management (RM) algorithm and the other that need to be identified using real-time system identification techniques. The reconfiguration carried out for the former is termed as passive FTFC, whereas the latter as active FTFC.