Aircraft Fault Detection, Isolation and Reconfiguration in the Presence of Measurement Errors

Abstract

This paper discusses the efiect of measurement errors on the fault detection, fault isolation and control law reconflguration algorithms that Honeywell has been researching and developing together with NASA Langley Research Center (LaRC) under NASA’s Aviation Safety and Security Program. In our previous papers, we developed fault detection, fault isolation, pilot cueing and control law reconflguration algorithms for a civil transport aircraft, and evaluated the performance of our algorithms in piloted simulation in the Integration Flight Deck facility at NASA LaRC. However, we did not explicitly evaluate the efiect of measurement errors (that is, sensor noise, bias, and dynamics) on the performance of our algorithms. In this paper, we add sensor models to LaRC’s simulation model and evaluate the performance of our algorithms in the presence of measurement errors. Each algorithm is analyzed separately, and is enhanced by redesigning and/or re-tuned as necessary. The key contribution is that we provide theoretical justiflcation for the architecture of our fault detection algorithm and discuss a systematic procedure for tuning its gains, and we adapt and re-tune our fault isolation algorithm so that it can cope with measurement errors. We also provide results from batch simulations that are representative of the achieved performance in the presence of imperfect measurements.