Neural Networks Based Aircraft Fault Tolerant Control

Lunlong Zhong (1) , Felix Mora-Camino (2)

1 MAIAA - ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l'Aérien
2 LAAS-DISCO - Équipe DIagnostic, Supervision et COnduite

The purpose of this communication is to deal with the case in which an aerodynamic actuator failure occurs to an aircraft while it has to perform guidance maneuvers. The problem considered deals with the reallocation of redundant actuators to perform the required maneuvers and maintain the structural integrity of the aircraft. A Nonlinear Inverse Control technique is used to generate online nominal moment along the three axis of the aircraft. Then, taking into account all material and structural constraints as well as the redundant effects from other actuators, a Mathematical Programming problem to be solved is considered. The proposed solution method is based on dynamic neural networks which appear to provide acceptable response times. Simulation results are displayed and new development perspectives are discussed.

Domaines: Sciences de l'ingénieur [physics]; Automatique / Robotique

Lunlong Zhong, Felix Mora-Camino. Neural Networks Based Aircraft Fault Tolerant Control. ATIO 2012, 12th AIAA Aviation Technology, Integration, and Operations Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Sep 2012, Indianapolis, United States. pp xxxx, ⟨10.2514/6.2012-5683⟩. ⟨hal-00926483⟩