Probing the NASA generic transport aircraft in real-time for health monitoring

This paper investigates the effectiveness of a pseudo-random binary sequence as a probing signal for real-time monitoring of a closed-loop nonlinear GTM aircraft (NASA generic transport model). Two forms of probing outputs based on two probing algorithms are studied: a small signal pulse response matrix at trim using pulse-compression, and a linearized state-space parameter set using regression. A new structure of the pulse-compression method is introduced to simultaneously monitor the small signal pulse sequences for all input-output channels of the aircraft, and the probing algorithm is implemented on a Virtex-5 FPGA evaluation platform for speed. The paper also exploits the role of the probing signal in regression to identify a local state-space model for GTM as the first step in our effort toward real-time faulty model identification to support flight envelope assessment. The pseudo random sequence probing compares favorably to white noise and doublet excitations. Probing outputs in both forms are shown to be highly sensitive to the occurrence of actuator faults in the plant.