关键词: 支持向量机, 建模, 直升机旋翼, 序列最小优化, 仿真模型

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