Dynamic Modeling Method Based on Support Vector Machine

Neural networks with good nonlinear mapping abilities can be applied to build simulation model of helicopter. But they have some difficulties such as hardness of selecting network structure, slow convergence speed, local minimum, and over-fitting. To avoid above problems, a modeling method for dynamic nonlinear system based on support vector machine was proposed. This method was applied to build simulation model of helicopter. Compared with neural network model, SVM model possess some advantages such as simple structure, fast convergence speed and high generalization ability.