An approach of pondered individual analysis method in aircraft control

摘要

Loss of control in-flight is the cause of 70 of all the fatalities occurring in aircraft with a take-off mass greater than 5,700 kg, and human error is present in 55 of these incidents. The relevance of this subject provokes the technical and scientific communities and leads to a series of discussions, generating norms, procedures, and devices that seek to mitigate the causes of these accidents. To contribute to the aeronautical sector, concerning the development of new strategies that seek to minimize the number of fatal air accidents, this work proposes the use of a new control architecture based on the combination of neuro-fuzzy systems in automatic aircraft control. For that matter, a new fuzzy inference method, called PIA (Pondered Individual Analysis), is used, which combines intuitiveness and high computational performance in the process of mathematical translation of the rule base involved in the process. The results of longitudinal and lateral-directional dynamics obtained in the simulation of a Cessna 172 aircraft are analyzed and compared to those obtained with the proportional integral derivative controller and with the neuro-fuzzy controller that uses the Takagi-Sugeno fuzzy inference method. They present a lower mean absolute error in relation to the reference signals, thus showing the high performance of the PIA method, which proves to be an effective tool to be considered in solving problems in the control area.