Review on uncertainty analysis and information fusion diagnosis of aircraft control system

In the aircraft control system, sensor networks are used to sample the attitude and environmental data. As a result of the external and internal factors (e.g., environmental and task complexity, inaccurate sensing and complex structure), the aircraft control system contains several uncertainties, such as imprecision, incompleteness, redundancy and randomness. The information fusion technology is usually used to solve the uncertainty issue, thus improving the sampled data reliability, which can further effectively increase the performance of the fault diagnosis decision-making in the aircraft control system. In this work, we first analyze the uncertainties in the aircraft control system, and also compare different uncertainty quantitative methods. Since the information fusion can eliminate the effects of the uncertainties, it is widely used in the fault diagnosis. Thus, this paper summarizes the recent work in this aera. Furthermore, we analyze the application of information fusion methods in the fault diagnosis of the aircraft control system. Finally, this work identifies existing problems in the use of information fusion for diagnosis and outlines future trends.