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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2009, Vol. 30 ›› Issue (1): 46-51.

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Modeling for Landing Process of Helicopter with Rotator Self-rotating Based onModified SMO Algorithm of Support Vector Machine

Wang Shuzhou1,San Ye1,Zhang Yunchang2   

  1. 1. Control and Simulation Center, Harbin Institute of Technology;
    2. The Flight Simulation Research Institute of Air Force
  • Received:2007-10-31 Revised:2008-03-07 Online:2009-01-25 Published:2009-01-25
  • Contact: Wang Shuzhou

Abstract:

Aimed at building simulation model of helicopter with high precision, the support vector machine (SVM) method is introduced to the field of intelligent modeling for a helicopter. A simulation model of a helicopter with rotator self rotating for the landing process is built. The global minimum of a quadratic programming will be reached when the dual gap is zero. According to this feature, the halt criteria in the sequential minimal optimization algorithm is modified, and the modified algorithm is applied to training the SVM simulation model. Compared with neural network model, it is shown by simulation results that the SVM simulation model of helicopter possesses some advantages, such as simple structure, fast convergence speed and high generalization ability.

Key words: support vector machine, modeling, helicopter rotors, sequential minimal optimization, simulation model

CLC Number: