Flight control strategy for jet transport in severe clear-air turbulence based on flight data mining

Abstract

This paper presents a new concept of the control strategy in prevention program for the airlines to prevent the injuries of passengers and crew members for transport aircraft. A twin-jet transport aircraft encountered severe clear-air turbulence at transonic flight in descending phase is the study case of the present paper. The nonlinear and unsteady flight controllability models based on flight data mining and the fuzzy-logic modeling of artificial intelligence technique, are utilised to support this new concept. The proposed flight controllability models with the function of nonlinear dynamic inversion are employed to provide flight control strategy through flight simulations of dynamic inversion process; it is an innovation in mathematical modelling of aerospace engineering. Since the sudden plunging motion with the abrupt change in attitude and gravitational acceleration (i.e. the normal load factor) to affect the flight safety the most, hazard mitigation is a great concern for the aviation community. The present study is initiated to examine possible mitigation concepts of accident prevention to provide a training course for loss of control in-flight program to the airlines.