Turbulence Encountered Landing Control Using Hybrid Intelligent System

  • Jih-Gau Juang
  • Hou-Kai Chiou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)


During a flight, take-off and landing are the most difficult operations in regard to safety issues. Aircraft pilots must not only be acquainted with the operation of instrument boards but also need flight sensitivity to the ever-changing environment, especially in the landing phase when turbulence is encountered. If the flight conditions are beyond the preset envelope, the automatic landing system (ALS) is disabled and the pilot takes over. An inexperienced pilot may not be able to guide the aircraft to a safe landing at the airport. This paper proposes an intelligent aircraft automatic landing controller that uses recurrent neural network (RNN) controller with genetic algorithm (GA) to improve the performance of conventional ALS and guide the aircraft to a safe landing.


Pitch Angle Recurrent Neural Network Wind Turbulence Genetic Algorithm Search Hybrid Intelligent System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jih-Gau Juang
    • 1
  • Hou-Kai Chiou
    • 1
  1. 1.Department of Communications and Guidance EngineeringNational Taiwan Ocean UniversityKeelung CityTaiwan,ROC

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