Deep recurrent and convolutional networks for robust fault tolerant autonomous landing control system design under severe conditions

M. Cagatay Sahin, Batuhan Eroglu, Nazim Kemal Ure, Huseyin Burak Kurt

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)


Developing a control system that is tolerant to actuator and sensor faults is one of the major problems in flight control system design. In many failure scenarios, it is too dangerous to continue the mission and hence aircraft is ordered to perform an emergency landing. Thus, it is critical that an autonomous landing system should be capable of landing the aircraft under severe actuator and sensor failures and external disturbances such as wind. In this paper, based on previous work, we present a robust nonlinear dynamic inversion based landing control system that can accommodate actuator failures and wind disturbances. We further improve the performance of the system by using a deep recurrent network to estimate the air-data parameters such as angle of attack, when the pitot tube measurements are unavailable/noisy. Simulation results show that the developed system is able to land the aircraft safely for a wide variety of failure and wind disturbance scenarios. In particular, use of a deep neural network makes a considerable difference in severe wind conditions.

Original languageEnglish
Title of host publicationAIAA Scitech 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105784
Publication statusPublished - 2019
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: 7 Jan 201911 Jan 2019

Publication series

NameAIAA Scitech 2019 Forum


ConferenceAIAA Scitech Forum, 2019
Country/TerritoryUnited States
CitySan Diego

Bibliographical note

Publisher Copyright:
© 2019 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.


This work was supported by Turkish Aerospace Industries (TAI) through Advanced Aircraft Concepts Technology Center (GeHAKT).

FundersFunder number
Turkish Aerospace Industries
Thailand Automotive Institute


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